Scholarly article on topic 'Soil erosion planning using sediment yield index method in the Nun Nadi watershed, India'

Soil erosion planning using sediment yield index method in the Nun Nadi watershed, India Academic research paper on "Agriculture, forestry, and fisheries"

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Abstract of research paper on Agriculture, forestry, and fisheries, author of scientific article — Hasan Raja Naqvi, A.S. Mohammed Abdul Athick, Hilal Ahmad Ganaie, Masood Ahsan Siddiqui

Abstract The study identifies the extent of soil loss and proposes a method for prioritization of micro-watershed in the Nun Nadi watershed. The study used the Sediment Yield Index (SYI) method, based on weighted overlays of soil, topography, rainfall erosivity and land use parameters in 24 micro watersheds. Accordingly the values and thematic layers were integrated as per the SYI model, and minimum and maximum sediment yield values were calculated. The priority ranks as per the sediment yield values were assigned to all micro-watersheds. Then the values were classified into four priority zones according to their composite scores. Almost 14 percent area of three micro-watersheds (SW5b, SW6a and SW7b) showed very high priority; approximately 30.57 percent of the study area fell under the high priority zones. These areas require immediate attention. Conservation methods are suggested, and the locations of check dams are proposed after considering drainage, slope and soil loss.

Academic research paper on topic "Soil erosion planning using sediment yield index method in the Nun Nadi watershed, India"

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International Soil and Water Conservation Research ■ (■■■■) lll-lll

www.elsevier.com/locate/iswcr

Soil erosion planning using sediment yield index method in the Nun

Nadi watershed, India

Hasan Raja Naqvia,n, A.S. Mohammed Abdul Athicka, Hilal Ahmad Ganaieb, Masood

Ahsan Siddiquic

aDepartment of Geomatics Engineering (School of Engineering), Adama Science & Technology University, P.O. Box 1888, Adama, Ethiopia Department of Geography, Government College for women, Udhampur, India cDepartment of Geography, Jamia Millia Islamia (A Central University), New Delhi 110025, India Received 5 April 2015; received in revised form 21 June 2015; accepted 25 June 2015

Abstract

The study identifies the extent of soil loss and proposes a method for prioritization of micro-watershed in the Nun Nadi watershed. The study used the Sediment Yield Index (SYI) method, based on weighted overlays of soil, topography, rainfall erosivity and land use parameters in 24 micro watersheds. Accordingly the values and thematic layers were integrated as per the SYI model, and minimum and maximum sediment yield values were calculated. The priority ranks as per the sediment yield values were assigned to all micro-watersheds. Then the values were classified into four priority zones according to their composite scores. Almost 14 percent area of three micro-watersheds (SW5b, SW6a and SW7b) showed very high priority; approximately 30.57 percent of the study area fell under the high priority zones. These areas require immediate attention. Conservation methods are suggested, and the locations of check dams are proposed after considering drainage, slope and soil loss. © 2015 International Research and Training Center on Erosion and Sedimentation and China Water and Power Press. Production and Hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Check dam; Prioritization; Nun Nadi watershed; Soil loss; SYI

1. Introduction

Soil is one of the crucial natural resources that support life on the earth and controls the economic conditions of the nation. Soil erosion is a serious global problem that not only threatens sustainable agriculture but also ecosystems (Jain, Mishra, Surendra, & Shah, 2010). However, with rainfall erosion, the eroded soil moves downstream in the form of sediments. The amount of sediment load passing through the outlet of a watershed is known as sediment yield (Bhuyan, Marjen, Koelliker, Harrington, & Barnes, 2002)

The process of soil formation takes many centuries, but with rainfall erosion this can be negated in a few major storms, leaving soils residues that are degraded resulting in reduced yields. Soils erosion is common in all areas of the world, but developing countries suffer more because of the inability of their farming populations to replace lost

*Corresponding author. Tel.: + 251 22 110 00 48; fax: + 251 22 112 01 50. E-mail addresses: naqvi.hassan7@gmail.com (H.R. Naqvi), oceanathick@yahoo.co.in (A.S.M.A. Athick), jmi.hilalahmad@gmail.com (H.A. Ganaie), siddiqui_jmi@yahoo.co.in (M.A. Siddiqui). Peer review under responsibility of IRTCES and CWPP

http://dx.doi.org/10.1016Zj.iswcr.2015.06.007

2095-6339/© 2015 International Research and Training Center on Erosion and Sedimentation and China Water and Power Press. Production and Hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

soils and nutrients (Erenstein, 1999). Therefore, sustainable land management practices are urgently needed to preserve the production potential of land.

The efficient and optimum management and conservation of soil, land and water resources is best approached on a watershed basis. Normally, the amelioration processes are developed and applied following prioritization and landscape planning. Prioritization plays a key role in identifying areas that require attention (Kanth & Zahoor-ul, 2010). Watersheds are those areas from which runoff resulting from precipitation flows past a single point into a large stream a river, lake or an ocean. These are natural hydrologic entities that cover a specific aerial extent of land from which rainwater flows to a defined gully, stream or river of a particular point (Kumar & Kumar, 2011). The size of the watershed is dependent on the size of interception of the stream or river and the drainage density and its distribution. The drainage network helps in delineation of watershed for a particular river system. The Watershed Atlas of India published All India Soil & Land Use Survey, Ministry of Agriculture and Cooperation, Govt. of India (1990) has been referred for delineation from watershed to micro-watershed level.

There are several empirical models based on geomorphological parameters that were developed in the past to quantify sediment yield resulting from erosion. In addition, other methods such as Sediment Yield Index (SYI), developed by Bali and Karale (1977), and the Universal Soil Loss Equation (Wischmeier & Smith, 1978) are extensively used for prioritization of watersheds.

Chakraborti (1991) employed the SYI method for predicting sediment yield for prioritization of watersheds using remote sensing data. Similarly, Ratnam, Srivastava, Rao, Amminedu, and Murthy (2005) also employed the SYI model to analyze run off quantity, prioritize small watersheds and locate the check dam sites for the conservation of soil. Micro-watersheds are suitable for estimating sediment yield, prioritizing on the basis of sediment loss, and providing information for decision makers (Food and Agricultural Organization, 1987). However, by analyzing micro-watersheds in a GIS environment, results can be extrapolated for large areas. For instance, Mellerowicz, Ress, Chow, and Ghanem (1994) reported delineation of erosion prone areas and prioritization of micro-watersheds for a targeted and cost-effective conservation planning purpose.

Prioritized erosion and sediment yield data can also be used to locate check dams. Durbuda, Purandara, and Sharma (2001) suggested suitable site locations for check dams by studying run-off in part of the Mahi River. The study achieved the objectives of calculating the sediment yield index for soil loss estimation, prioritizing the micro-watersheds on the basis of sediment yield values and recommending the position of check dams and other conservation practices for soil conservation.

2. Study area

The Nun Nadi Watershed (NNWs) is a part of Yamuna river catchment. It extends between 30° 20' 08" to 30° 28' 18" N latitude and 77° 58' 36'' to 78° 06' 21'' E longitude and covers an area of about 8697.33 ha (Fig. 1). The watershed is located in the Doon Valley region, and according to previous studies approximately 20 Mg/ha/yr soil is removed, making it highly prone to soil erosion (Singh, Babu, Narain, Bhushan, & Abrol, 1992). The area has a subtropical climate with cold winters, warm and crisp springs, hot summers and a strong monsoon. It is surrounded by the Himalayas in the North. The average temperature of the study area is 20 °C approximately. The average annual rainfall of Dehradun station is 2073.3 mm, with about 87 percent of the annual rainfall in the area received during the months of June to September (July and August are the rainiest months). The variation in the rainfall from year to year in the area is appreciable. The average precipitation of Dehradun station in study area was 1554 mm in 2009 and recorded almost 3000 mm in 2013 (http://en.tutiempo.net/climate/ws-421110.html).

The study area includes the Dehradun and Mussorrie stations for rainfall data, but for better accuracy the neighboring stations viz. Nainital, Gopeshwar, Mandal, Garigaon, Lambgarh, Pandukeswar, and Joshimath were also marked as point layers, and were subsequently interpolated applying the Inverse Distance Weighted (IDW) method.

3. Data and methodology

The Survey of India (SOI) toposheets number 53F/15, 53J/2 and Landsat-TM image of October 2009 were the main sources of data for the study. Toposheets were used not only to delineate the watershed and micro-watersheds,

78°0'0"E 78c3'0"E 78WE

Drainage Network N

78°0'0"E 78°3'0"E 78°6'0"E

Fig. 1. Location of Nun Nadi Watershed.

Fig. 2. Schematic flow chart for micro-watershed prioritization.

but also for the preparation of the base map containing information about drainage, contours, etc. The satellite images were used to prepare a land use/land cover map. Rainfall data for the study period were procured from the Indian Meteorological Department (IMD), Dehradun. Other relevant data were obtained from published and unpublished records. Fig. 2 describes the methodology for the study.

3.1. Sediment yield index (SYI)

The SYI method is highly useful for prioritization of micro-watersheds according to erosion impact. In this study several important parameters were considered (Table 1), including land use/land cover, soil type, and landscape drainage.

Map layers were prepared for each parameter and used for assigning weighted values to calculate the SYI in tkm_2 yr_ 1 according to the following equation:

Sediment yield index (SYI) = x Wt x A) x 100/Aw (1)

where, i — 1-n;

At — area of ith unit (EIMU);

Wi — weighted value of ith mapping unit;

Di—delivery ratio;

n — no. of mapping units (this is Dt in the equation); Aw total area of sub/micro-watershed.

The rate of soil loss was estimated for each micro-watershed, and then ranked into four priority ranking classes (very high, high, medium and low) according to the SYI values.

Several map layers were prepared to determine the Wt in SYI model. Firstly, the weighted values for every factor were assigned on the basis of their risk level, then input into the SYI equation. Priority indicators and the composite score for each micro-watershed were assigned according to Table 2. The weighted values were assigned using the weighted overlay tool in Arc Map.

There are different ways by which the suitability assessment can be done. There have been studies of suitability assessment employing a "maximization" or "worst case" model (Space Applications Centre, 1999), where the "worst" parameter determines the suitability. As a result, a relatively less important parameter could determine the suitability in the final analysis. This anomaly arises because all parameters are considered to be of equal importance. Table 2 shows the criteria for adoption, the weighted values, and the total values that were applied for Wi in the above equation (1) for SYI calculation.

Table 1

Indicators used for SYI calculation.

S. no. Parameter Source

Criteria adopted for weightage values

1. Barren/bare Derived from LANDSAT land

2. Dense Derived from LANDSAT™ forest

3. Soil texture Kumar and Sharma (2005)

4. Topography SOI Toposheets on 1:50,000

5. Drainage SOI Toposheets on 1:50,000

6. Rainfall Indian Meteorology

Department, Dehradun (2009)

It is a direct result of human interference in environmentally fragile areas. More the coverage of barren land, higher the weightage value.

Since vegetation is a crucial natural resource that can also function as an environmental indicator, the dense forest cover of a region is an important indicator expressing the level of human impact. More the Dense Forest coverage, lower the weightage value has been assigned.

Soil texture is a very important parameter in terms of soil loss calculation. High value has been assigned for sandy loam texture.

Slope always plays an important role which directly impacts on soil with the amount of rainfall. It can vary according to slope steepness and length. Higher the elevation, higher the weightage.

Drainage density/number of streams has a direct bearing on soil erosion leading to highly dissected landscape. Greater the Drainage Density or number of streams, higher the weightage.

Rainfall is the most important factor that determines the soil loss rate. Higher the rainfall, higher the weightage values were assigned.

Table 2

Assigned weightage values of all factors for SYI calculation.

S. no. Parameters/factors Categories/classes Assigned weightage values

1 Rainfall 473-495 2

495-518 4

518-540 6

540-563 8

2 Slope (in deg.) 0-20 2

20-40 4

40-60 6

60-80 8

3 Soil texture Gravel sandy loam 2

Loam 4

Sandy loam 6

4 Forest land (values in percent) 0-25 8

25-50 6

50-75 4

75-100 2

5 Bare/barren land (values in percent) 0-25 2

25-50 4

50-75 6

75-100 8

4. Results and discussion

4.1. Land use/land cover (LULC)

Dense vegetation covered 1902.72 ha, 21.88 percent of the study area, while sparse vegetation covered approximately 3145.83 ha, about 36.17 percent of the area, and built-up areas occupied about 1158 ha (13.32 percent) area of the watershed. This distribution increased drastically after the declaration of Dehradun as the capital of Uttrakhand. Water bodies encompassed 495.36 ha (5.7 percent) of the total land area. Agricultural land covered 695.97 ha, about 8.00 percent of the total land, with fallow land occupying 391.77 ha or 4.50 percent of the total land area of watershed, and scrub land covered 567.9 ha or 6.53 percent land of the study area. On the other hand, bare soil/barren land occupied 338.94 ha or 3.90 percent land of the area. Detailed information about the area under different land use classes are shown in Fig. 3(e) and Table 3. Accordingly the weighted values are assigned on the basis of different micro-watersheds under the Nun Nadi watershed.

The status of LULC in the year 2009 indicates that the sparse and dense vegetation classes are dominant among all land cover types. Due to its proximity to Dehradun city, the watershed is negatively influenced by increasing population and development. By comparing LULC status of 2000 (Table 3), it was noticed that the changes occur primarily due to human disturbance. Built up areas have significantly increased (Naqvi, Mallick, Devi, & Siddiqui, 2013) on the Mussorrie hills, due to the construction of hotel/restaurants to accommodate tourists. Local population is encroaching on forest lands, and converting these for agricultural purposes.

4.2. Delivery ratio

Delivery ratio has been calculated on the basis of nearest stream (drainage density) distance in kilometers. The values of delivery ratio were assigned according to the length of the stream. In the study area most of the micro-watersheds were assigned 0.9 and 1.0 value from delivery ratio as per the drainage density. In this study, most of the streams are not more than 2 km.

H.R. Naqvi et al. / International Soil and Water Conservation Research I (IIII) III III

Fig. 3. Slope in degree (a), drainage map (b), rainfall erosivity (c), different soil textures (d), and land use (e) maps have been prepared for assigning the weightage values to calculate the SYI.

Table 3

LULC area under different classes.

Land use land cover classes Area in hectare (2000) Area (%) Area in hectare(2009) Area (%)

Dense vegetation 2220.21 25.53 1902.72 21.88

Sparse vegetation 3233.34 37.18 3145.83 36.17

Built-up 450.72 5.18 1158.84 13.32

Water bodies 285.75 3.29 495.36 5.70

Scrub land 689.13 7.92 567.9 6.53

Agricultural cropland 867.87 9.98 695.97 8.00

Fallow land 538.83 6.20 391.77 4.50

Bare soil/barren land 411.48 4.73 338.94 3.90

Total 8697.33 100.00 8697.33 100

4.3. Soil type

Sandy loam soils are the dominant soil class in the study area, covering about 5431.76 ha or around 62.45 percent of the total area. Gravelly and loamy soils occupied 2069.12 (23.79 per cent) and 1196.45 (13.76 per cent) hectares of the study area, respectively. Higher weighted values have been assigned for sandy loam soils [Fig. 3(d)] because these can be eroded easily in comparison to other soil types in the study area.

4.4. Rainfall erosivity

Rainfall is the most important determining factor for soil loss. The values of selected stations were interpolated and categorized into classes, with higher weighted values assigned to regions receiving high rainfall. The rainfall erosivity factor has been calculated by the equation suggested by Renard, Foster, Weesies, Mccool, and Yoder (1997), with minimum and maximum values calculated at 1478.25-2097.53 MJ mmha_ 1 h_ 1 yr_ 1 [Fig. 3(c)], with rainfall values of 456 and 573 mm respectively.

4.5. Slope in degree

Slope is a key factor affecting the rate of soil loss. Areas in high altitude positions were assigned higher weighted values [Fig. 3(a)].

4.6. Calculated SYI values for micro-watershed prioritization

Table 4 and Fig. 4 give detailed information about the input values, prioritization ranking and prioritization categories/zones of the different micro-watersheds.

The micro-watersheds were broadly classified into four priority zones according to their composite scores as per the minimum and maximum values calculated by SYI model in study. Classes were very high ( > 1200), high (8001200), medium (400-800), and low (< 400). A map of micro-watershed prioritization was prepared according to these values, as shown in Fig. 4. This map identifies the micro-watersheds requiring priority conservation treatment.

Micro-watersheds, SW6a, SW7b and SW5b were assigned very high priority, with values of 1362.96 and 1349.04, 1236.18 sediment yield, respectively. Most of the lands in these micro-watersheds are covered by dense forest, built-up and agricultural land. Some areas fall under the bare/barren land, imparting high sensitivity to water erosion.

Micro-watersheds SW1a, SW1b, SW2c, SW3a, SW4a, SW5a, SW6b and SW7a were assigned high priority. Micro-watersheds SW1a, SW1b, SW2c and SW3a are not as heavily forested, but have some settlement and bare/ barren land. However, micro-watershed SW4a and SW5a are covered with bare soil/barren land on the Mussorrie hills, with SYI values of 971.62 and 1112.00, respectively.

Micro-watersheds SW2a, SW3b, SW4b, SW4c, SW8b, SW8c, SW9a and SW9c were rated in the medium category. These ratings are due to the substantial forest cover; moderate extent of built-up, agricultural, and barren land. The sediment yield values for all such micro-watersheds are 685.55, 763.27, 643.07, 768.16, 401.81, 758.46, 411.59 and 547.73 t km"2 year"1

The micro-watersheds with the lowest priority ranking are SW2b, SW3c, SW8a, SW8d and SW9b, which cover an area of about 14.74 percent (Table 5) of the Nun Nadi Watershed. In these micro-watersheds, except SW8a and SW8d, dense forest cover is substantial. Good coverage of vegetation prevents soil loss and hence these are assigned the least priority for conservation.

4.7. Proposed soil conservation techniques

During the field survey, it was observed that some sites suffered huge soil loss in the form of landslides, gully erosion, etc. related to the presence of bare/open land, as shown in (Fig. 5). Several factors can be attributed to the soil loss incurred in these locations, including bad agricultural practices, human encroachment into vegetated areas, increasing population pressure and lack of awareness. These practices degrade the quality of the soil in the Nun Nadi watershed, resulting in increased vulnerability to erosion.

Table 4

SYI Values of micro watersheds with priority ranks.

SW MWS Area in sq/km Weightage value Weightage product Delivery ratio SYI value Priority rank

SW1 SW1a 2.01 19 38.19 1.00 850.56 11

SW1b 2.48 22 54.56 0.90 1093.63 5

SW2 SW2a 2.93 23 67.39 1.00 685.55 15

SW2b 2.15 18 38.70 1.00 393.69 20

SW2c 4.84 21 101.64 0.90 932.50 7

SW3 SW3a 3.34 19 63.46 1.00 910.47 9

SW3b 2.66 20 53.20 1.00 763.27 13

SW3c 1.47 15 22.05 1.00 316.35 23

SW4 SW4a 4.80 26 124.80 0.90 971.62 6

SW4b 3.70 24 88.80 1.00 768.16 12

SW4c 3.30 19 62.70 1.00 643.07 16

SW5 SW5a 4.17 26 108.42 1.00 1112.00 4

SW5b 5.58 24 133.92 0.90 1236.18 3

SW6 SW6a 3.20 23 73.60 1.00 1362.96 1

SW6b 2.20 22 48.40 1.00 896.30 10

SW7 SW7a 2.75 21 57.75 1.00 919.58 8

SW7b 3.53 24 84.72 1.00 1349.04 2

SW8 SW8a 3.21 19 60.99 1.00 382.38 21

SW8b 3.77 17 64.09 1.00 401.81 19

SW8c 5.71 17 97.07 0.90 547.73 17

SW8d 3.26 16 52.16 1.00 327.02 22

SW9 SW9a 4.80 17 81.60 0.90 411.59 18

SW9b 2.73 15 40.95 1.00 257.38 24

SW9c 8.38 16 134.08 0.90 758.46 14

86.97 1753.24 18291.30

Fig. 5(a) illustrates a landslide in the study area. Although these are natural phenomena leading to soil loss, human activities further aggravate this problem. Consequently, there are noticeable increases in the landslide frequency due to the unplanned developmental activities on the upper reaches of the micro-watersheds. Similarly, Fig. 5(b) illustrates the impacts of poor agricultural practice on steep slopes resulting in aggravated soil loss and minimized crop yields.

During the field survey, some conservation practices were observed, but which unfortunately were adequate for amelioration of the problem. However, these were limited to only a few sites and some locations, mostly located on river terraces with bounded gabion boxes and stone walls. These few interventions have been implemented by the government, but the majority of the area remains untouched in terms of conservation interventions.

Gabion boxes play a major role in soil loss protection, as shown in Fig. 6(a). They were constructed using stones and wires along the river banks. Alternately, stone walls were built on gullies with steep slope but only few such sites were observed during the field visit [Fig. 6(b)].

78°0'0"E 78°3'0"E 78°6'0"E

78°0'0"E 78°3'0"E 78°6'0"E

Fig. 4. Micro-watershed prioritization using the SYI model.

Table 5

Micro watersheds under different priority zones.

Priority categories Priority classes SYI values Micro-watersheds Area in per cent

Very high I > 1200 SW5b, SW6a and SW7b 14.15

High II 800-1200 SW1a, SW1b, SW2c, SW4a, SW3a, SW5a, SW6b and SW7a 30.57

Medium III 400-800 SW2a, SW3b, SW4b, SW4c, SW8b, SW8c, SW9a and SW9c 40.53

Low IV < 400 SW2b, SW3c, SW8a, SW8d and SW9b 14.74

Fig. 5. (a) Land slide (Quartzite rocks) near Mussorrie settlements and (b) poor agricultural practice in the Nun Nadi watershed.

More extensive application of simple, cost effective conservation interventions, such as contour farming, cover crops, conservation agriculture, check dams, channeled terraces, grass strips, social forestry, etc. can significantly contribute to mitigation of soil erosion and protection of the soil. Social forestry and development of fodder grasses near settlement areas, contour bunding in agricultural fields and steps drain techniques are some conservation practices that are proposed for implementation in the study area. Better training of farmers can improve adoption of conservation measures with ultimate improvement of crop production. Bare land areas should be covered with fodder

10 H.R. Naqvi et al. / International Soil and Water Conservation Research I (IIII) III III

Fig. 6. (a) Gabion boxes along river sides and (b) stone walls for minimizing the soil loss.

78°0'0"E 78°3'0"E 78°6'0"E

78°0'0"E 78°3'0"E 78°6'0"E

Fig. 7. Selected sites for check dams.

grasses and other cover crops to reduce the impacts of corrosive rainstorms and soil erosion, especially on high elevated areas (1600-2000 m). Concurrently, governments should implement strong policies and conduct awareness programs about the illegal encroachment in natural vegetation regions.

Some sites are suggested for the construction of check dams that can potentially minimize soil loss rate in the study area (Fig. 7). The map of slope, drainage, SYI values and rate of soil loss using RUSLE were overlaid and the positions of check dams are determined.

5. Conclusion

In this study, the SYI method was used to calculate soil loss in micro-watershed in the study area. Thematic layers of all parameters for the SYI model were mapped. The micro-watersheds SW5b, SW6a and SW7b were identified as being very high risk. This class covers approximately 14.15 per cent (12.31 km2) of the total land of Nun Nadi watershed; instant attention is required to conserve these locations.

Check dams are suggested in regions where the soil loss is significantly high compared to the other areas. The positions of check dams are identified by overlaying drainage [(Fig. 3(b)] and slope maps on regions which are

highly susceptible severe to soil loss. The study comments on conservation techniques that can be adopted. Such studies can be similarly adopted for other watersheds, where soil erosion is severe.

One of the major causes for erosion in the study area is construction of buildings on higher reaches near the Mussorrie hills, and encroachment agriculture into vegetated areas. Developmental activities on bare land disturb the natural drainage and contribute directly and significantly to soil erosion.

Acknowledgment

We are thankful to Dr. Suresh Kumar of IIRS Dehradun for his consistent support. We are also grateful to Syed Umer Latief for his valuable suggestions. We are highly acknowledging the comments given by reviewers. Corresponding author is obliged to UGC for providing Non-Net fellowship during the research work.

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