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Using Multi - Criteria, AHP and Influence Approaches for Agriculture Development: A Case Study of Upper Mula Basin in Maharashtra (India)

Ravindra D. Gaikwad , Vijay S. Bhagat
Applied Ecology and Environmental Sciences. 2021, 9(3), 368-379. DOI: 10.12691/aees-9-3-7
Received February 14, 2021; Revised March 17, 2021; Accepted March 22, 2021

Abstract

Agricultural development is unique sign for development of agricultural base country. Multi-criteria, AHP and influence based analysis is suitable for agricultural development. Six criterions (Crops) sugarcane, vegetables, pulses, fruits, rice and grains were selected for development indicators of Upper Mula basin in Ahmednagar district, Maharashtra (India). Expert opinions for ranking the criterion selected for influence. Sugarcane, vegetables and fruits show higher influences on development of watershed arrangement in the study area. Further, crops grains and pluses were show significant influence in kharip season. Using AHP techniques for influences were calculated based on weights estimated. Normalized and distribution of specific crops using the values of influences within the sub-watersheds. Agriculture developments influence are classified into very low (< Mean-1STD), low (Mean-1STD to Mean), moderate (Mean to Mean + 1STD), high (Mean + 1STD to Mean + 2STD), and very high (Mean + 2STD<) and agricultural development are classified into high, moderate and low categories. The methodology is the effective tool for agricultural development of sub-watersheds.

1. Introduction

Agricultural development is one of the significant factors representing the overall development of the rural regions 1. Study area shows undulating surface and therefore varied agriculture and cropping pattern. The slope decreases towards the East from Western hilly region. Higher rainfall, steep slopes and dense forests are observed in western hilly which is the source of Mula River. Paddy and Nachani are important crops in this area. Further, sugarcane, vegetables and fruits are observed in the eastern where the slopes are less. Gumma 2 have used weighted integration of multiple thematic layers, Gassman 3, Daloglu 4 have used Soil and Water Assessment Tool, Panhalkar 5 had use intersect overlay technique with GIS environment, Daloglu 4 have used agent-based models (ABM) with combination Soil and Water Assessment Tool, Boumaa 6 have used water balance of irrigation systems for Agricultural development. Further, Analytical Hierarchy Process (AHP) based multi-criteria analysis and influence technique can be useful tool for quick agriculture development prioritization 7 of watersheds. The crops sugarcane, vegetables, pulses, fruits, rice and grains are economically useful crops select for the period 2016 to 2019 for agricultural development. Rice, Nachani and Varai is a rain fed crop grown in hilly slope and foothills area 8. However, due to the development of irrigation facilities in the area with reduced slope in the east, sugarcane, vegetables, fruits, Grains and pulses have changed. The area under mainly vegetable and fruit crops seems to have increased.

2. Study Area

Upper part of the basin Mula River (19° 03'45.00'' N to 19º 30'02.00'' N and 73º 33'45.00'' E to 74º 37'31.00'' E) in Ahmednagar district (India) distributed inside Akole, Sangamner, Parner and Rahuri tahshils was selected for agricultural development of sub-watersheds (Figure 1). The River Mula is main tributary of Pravara River and source region in Ajoba Dongar, near Harishandragad located in the Western Ghat. The height varies from 512 to 1472.7 m. and rainfall from 467 to 1505 mm. around 86.38% area classified in the class 0 to 10ºslopes. Geologically the study area is the part of Deccan trap with compound pahoehoe, and som Aa flows, basaltic and Alluvium. Somewhat deep, drained, and calcareous soils on gentle sloping with moderate erosion area are observed (1717.48km2). Further, 422.85Km2 area covered extremely drained, very shallow and deep, loamy soils, moderate, undulating land with strong stoniness and high erosion. Rice is the main crop in the kharip season for the Western part whereas Grains like Ragi, Nagali, Varai, and Barly, Pulses like Pigeon Peas Skinned (Toor), Green Gram Split (Moong), Black Gram (Udid), Moth Bean (Matk)i, Horse Gram (Hulga),Pink Lentil (Masur), Pawta, Chauli Field Bean (Wal), Ghevda and Groundnuts are observed as major crops in the kharip season and Jawar, Wheat, Maize and Sunflower, Vegetables like tomato, cabbage, green bean, cilantro, flowers, brinjal etc. in rabbi season for Eastern part. The Upper Mula basin has been divided into 140 sub watershed namely SW0 to SW139 (Figure 1) for analysis and agricultural development 9.

3. Methodology

Analytical Hierarchy Process (AHP) based multi-criteria analysis and influence technique were used for agriculture development of sub-watersheds in Mula River basin. The ranking (Table 7) of the crops have been performed based on expert opinions collected through remote technique e.g. googol forms. The agriculture development was performed through eight steps: 1) Delineation sub-watersheds with help of DEM, 2) Data collection and analysis for selected crops (criterion), 3) Ranking of the criterions, 4) Pairwise comparison matrix analysis, 5) Normalization of pairwise comparison matrix, 6) Calculations of weights, 7) Sub-watershed wise normalization of calculated influences, and 8) Calculation of agriculture development according to the sub-watersheds.

3.1. Data

Data regarding selected crops e.g. Rice, Sugarcane, vegetables, Grains, Pulses and fruits was procured from government records available at tehsil offices [Akole, Sangamner, Rahuri and Parner] in the district for the year of 2016 and 2019 and used for multi-criteria and AHP analysis to calculate agriculture development in the watershed. GIS layers were prepared based on topographic maps (47E/10, 47E/11, 47E/14, 47E/15, 47I/2, 47I/3, 47I/4, 47I/6, 47I/7, 47I/8, 47I/10, 47I/11 and 47I/12) procured from SOI [survey of India]. ASTER DEM data was used for delineation of watershed boundaries. The data and maps were loaded in GIS software for preparation of layers.

3.2. Criterions

Rice, Sugarcane, vegetables, Grains, Pulses and fruits were used for multi-criteria analysis using AHP and influence technique to calculate the agriculture development in the study area. The study area has naturally varies of rainfall, slope and soil. Rice, Sugarcane, vegetables, Grains, Pulses and fruits are economically important and principal crops in study area. Therefore, criterions (crops) selects for agriculture development.


3.2.1. Rice

In western part of the study area located in hilly and mainly tribal community live in hilly area. Rice is an important crop in Kharip Season and covered 24.50% area under the Rice cultivation in western hilly region with higher rainfall 8. Watersheds in the western part of the region were showed the highest area under rice and no rice cultivation was found in the area with less rainfall in the East. About 2.4% areas were changed from 2016 to 2019 (Figure 1). Paddy production has increased in the villages like Ambit Khind, Kauthewadi, Gondushi, Wanjulset and Manikozhar located in western part with moderate slope (20º to 30º), marginally deep and extremely drained loamy soils and slightly deep good drained well calcareous soils and moderate erosion.


3.2.2. Sugarcane

Sugarcane is a significant crop for tropical and sub-tropical regions 10 and economically important crop it has significant effect on the rural economy dependent on the sugarcane industry directly or indirectly 11 The impacts of growth of sugarcane production on the environment and society depend on the rural economy and high influence crop with significant positive and negative ecological and socio-economic impacts 12. Sugarcane is an important economic crop in the irrigated areas of the rain-fed region of Ahmednagar district. About 18 sub-watersheds 9.89% area show high and very high sugarcane production in downslope region in the east. Similar observation was reported by Kulkarni and Subramanian, 13 in case of sugarcane production in Mula and Mutha river basins, Maharashtra, India. In 2016, Mogras, Dhamangaon Pat and Kotul of Akole tehsil Shindodi Khambe, Darewadi, Bhojdari and Kumbharwadi in Sangamner tehsil and Jambhli in Rahuri tehsil show the highest sugarcane production. The statistics of 2019 shows 6 watersheds of the villages Shindodi Khambe, Darewadi, Bhojdari and Kumbharwadi in Sangamner tehsil Pangri of Akole tehsil and Jambhli in Rahuri tehsil) show the high sugarcane production (Table 2). However, sugarcane production has been decreased in the villages like Moguras, Dhamangaon Pat and Kotul in Akole tehsil from 2016 to 2019 and increased by 3.57% in the villages Shiswad, Pimpalgaon Khand, Sherewadi, Thakarwadi and Lingdev of Akole tehsil, Darewadi and Bhojdari villages of Sangamner tehsil and Jambhli in Rahuri tehsil. Further, the higher (0.40<) positive change was observed in 5 watersheds due to application of watershed development program in the areas on lesser slopes, deep soils and availability of irrigation facilities.


3.2.3. Vegetables

Vegetables are an important cash crop 14 in the study area. However, it is not grown in the hilly regions of the western part of the study area, the steep slope, forested regions and the highland areas. In the villages of Paithan, Ambhol and Kotul, due to the irrigation of Mula River, crops like tomato, cabbage, green bean, cilantro, flowers, bringal etc. are grown. In the low rainfall region of the eastern part vegetable crops are grown of the study area where irrigation facilities are available. In 2016, five watersheds including village Mahalwadi, Savargaon Ghule, Sarole plateau in Sangamner tehsil. Village Pimpalgaon Turk, Kanhur pathar, northern part of Karandi and Goregaon in Parner tehsil, have the very high production (0.65<) of vegetables. The villages of Belapur, Jachakwadi, Chaitanyapur, Jambhale, Brahnanwada and Kunthewadi in Akole tehsil high (0.40 to 0.65) production of vegetables (Table 3 and Figure 4). In 2019, Pangri, Kotul, Bholewadi and Mogras villages of Akole tehsil have the very high (0.57<) production of vegetables. Compared to 2016, vegetable production has increased in Belapur, Jachakwadi, Chaitanyapur, Jambhale, Brahnanwada and Kunthewadi villages are increase in production due to watershed programme and dam construction of Pimpalgaon on the Mula River. From 2016 to 2019, the most positive change in vegetable production is seen in Belapur, Jachakwadi, Chaitanyapur, Jambhale, Brahnanwada and Kunthewadi.  In 2019, Pangri, Kotul, Bholewadi and Mogras villages of Akole tehsil have the very high (0.38<) production of vegetables (Figure 4). Compared to 2016, vegetable production has increased in Belapur, Jachakwadi, Chaitanyapur, Jambhale, Brahnanwada and Kunthewadi villages due to increase in production due to watershed programme, increase irrigation facilities’  The use of new technologies for efficient irrigation like drip irrigation, sprinkler and use of mulching paper, availability of markets, fast transportation facilities and the economic awareness created among the farmers seem to have increased the vegetable production in the study area. From 2016 to 2019, the most positive change in vegetable production is seen in Belapur, Jachakwadi, Chaitanyapur, Jambhale, Brahnanwada and Kunthewadi.


3.2.4. Grains

Grains are an important crop in low rainfall and loamy soils. In western part of study area observed thin soils, steep slopes, and high rainfall in kharip season and grains like Ragi, Saya, Nagali, Rala, Varai, Katki, Bantti, Bhadali, Kodara and Barly are grown in this region. In rabbi season Wheat, Maize, Jwar and Bajara are grown in low rainfall region in Eastern part. In 2016, Shinde, Kohane, Vihir and Somalwadi in Akole tehsil and Karandi, Kinhi, Bahirobawadi, Pimpalgaon Turk in Parner tehsil have taken very high (0.26<) production of grains (Figure 5). The villages of Gondushi, Wanjulshet, Kauthwadi, Jamgaon, Chinchwane, Shelad, Padalne and Sakirwadi and Dhotre Khurd, Gajadipur, Wadgaon Satwal, Dhoki, Takli Dhokeshwar and Dhotre Budruk in Parner tehsil have increased the production of grains. In 2019, Dhotre Khurd, Gajadipur, Wadgaon Satwal, Dhoki, Takli Dhokeshwar and Dhotre Budruk in Parner tehsil have taken very high (0.28<) production of grains. However, compared to 2016, the production in Akole tehsil has decreased. In 2019 in Akole tehsil more laud use under vegetable cultivation compeer to 2016 because  use of new technologies for efficient irrigation like drip irrigation, sprinkler and use of mulching paper, availability of markets, fast transportation facilities and the economic  awareness created among the farmers. From 2016 to 2019, Khadki Budruk, Khadki Khurd, Purushwadi, Balthan, Savarkute, Dhamanvan, Shirpunje and Manikozhar in Akole tehsil and Dhotre Khurd, Gajadipur, Wadgaon Satwal, Dhoki, Takli, Dhokeshwar and Dhotre Budruk in Parner tehsil have seen positive change in grains production. In Akole tehsil Shiswad, Lavhali Kotul, Lavhali Ootur, Wagdari, Kothale, Somalwadi, Ghoti, Sakirwadi, Shelad villages, there has been a more positive change in the production of grains. From 2016 to 2019, Khadki Budruk, Khadki Khurd, Purushwadi, Balthan, Savarkute, Dhamanvan, Shirpunje and Manikozhar in Akole tehsil and Dhotre Khurd, Gajadipur, Wadgaon Satwal, Dhoki, Takli, Dhokeshwar and Dhotre Budruk in Parner tehsil have seen very high (0.04<) positive change in grains production (Table 4 and Figure 5). In Akole tehsil Shiswad, Lavhali Kotul, Lavhali Ootur, Wagdari, Kothale, Somalwadi, Ghoti, Sakirwadi, Shelad villages, there has been a high (0.02 to 0.04) positive change in the production of grains (Table 4).


3.2.5. Pulses

Pulses like Pigeon Peas Skinned (Toor), Green Gram Split (Moong), Black Gram (Udid), Moth Bean (Matk)i, Horse Gram (Hulga),Pink Lentil (Masur), Pawta, Chauli Field Bean (Wal), Ghevda, Bengal gram Whole (Harbara) and Green peas are an important crop in low rainfall and loamy soils. This crop is best grown in lowland northern and well drained soils in the hilly region. In western part of study area observed low soils, steep slopes, high rainfall in kharip season and pulses like Hulga, Pawta, Chauli Wal and Ghevda are grown in this region and eastern part of study area characterized unduael landforms, low rainfall and loamy soil and pulses like Toor,Moong, Udid, Matki,Hulga,Pawta, Chauli are grown in this region. In Parner tehsil, Kaknewadi, Dhotre Budruk, Hiware Korda, Tikol, Goregaon, Bhondre, Pimpalgaon, Turk and Kanhur  villages have produced very high (0.19<) pulses in 2016. Shiswad, Ambhol, Pisewadi, Shinde, Bholewadi and Palsunde have produced high (0.12 to 0.19) pulses in Akole tehsil and Darewadi, Kumbharwadi, Varwandi, Kauthe Malkapur, Khambe and Kharshinde villages in Sangamner tehsil have witnessed high (0.14 to 0.23) production of pulses in 2016 (Table 5 and Figure 6). Pulses production, however, was lower in other villages in the study area. There was no difference in the production of pulses between 2016 and 2019 due to increase in irrigation area, increase in production of vegetables and longer period required for production of pulses.


3.2.6. Fruits

Fruits are grown in medium slopes, fallow, moderately shallow soils and low Mango, Custard apple, Jackfruit, Aamla, Black berry, Jujubes and in agriculture the fruits which had been planted for getting income are Guava, Custard apple, Pomegranate, Chikoo, Banana, Papaya, Mango, Lemon, Watermelon and Grapes rainfall areas in the study area. In study are western part observed forest fruits like In 2016, Mhaswandi, Borbanwadi, Pemrewadi, Ambi Khalsa, Ghargaon, Sakur, Rankhambawdi, Kelewadi and Bambalewadi in 6 watershed areas of Sangamner tehsil and Vankute in one watershed area of Parner tehsil have produced very high (0.29<) fruits production (Table 6 and Figure 7). Out of the 16 villages in Sangamner tehsil and Parner tehsil which had higher fruit production in 2016, 11 watershed areas have moderate (0.07 to 0.18) fruit production in 2019. The main reason for the decline in fruit production in 2019 as compared to 2016 is that the watershed development work has increased the ground water level, created irrigation facilities, efficient irrigation like drip irrigation and sprinkler. However, Due to the new technology of water use, water consumption has been limited and timely irrigation facilities have been created for vegetables in summer, which has increased the area under vegetable production and reduced the area under orchards.

3.3. AHP for Analysis of Agriculture Development

Agriculture development of sub-watersheds was handled using AHP technique according to following steps: (1) determination of rank (Table 7) with help of expert opinion, (2) pairwise comparison, (3) normalization of pairwise comparison matrix of six crops, (4) calculation of weights and influence of crops, (5) normalization of sub- watershed wise influences of crops and (6) Agriculture development of sub- watersheds.


3.3.1. Determination Rank

Expert opinion with googol form methods were used for assigning the ranks (Table 7) to criterion selected for weighted analyses (Table 9). The correlation analysis is useful for better understanding of unstandardized factors than the standardized 15. Zolekar and Bhagat 16 have used export opinions for ranking the criteria’s in AHP based weighted overlay analysis for land suitability for agriculture development analyses. 1 to 6 ranks were assigned to selected crops (Table 7) 16, 17, 18, 19, 20 Scholars likes Sepehr 21, 22, Rekha 23 Feizizadeh 24, have been used multiple criteria decision-making and pair wise comparison matrix for agriculture development. Pairwise comparison matrix has been completed (Table 8) to calculate the weights for calculation of influence of criterion selected this study 16, 25. The PCM helps to recognize the association between the criterion in relation to ground water holding capacity, surface erosion and influence in assessment for applications of conservation techniques in the watershed for agriculture development 17, 25. The criterion values in PCM were divided by total of the column to find the cell values in normalized pairwise comparison matrix (Table 9).


3.3.2. Weights and Influences

Weights and Influences were calculated as average of values of criterions in row of normalized pairwise comparison matrix to get the weights of criterion 16, 26 (Table 9). Further, influences of the criterion selected for agriculture development of sub-watersheds were estimated by calculating the cell values (%) 27 (Equation 1) (Table 9).

(1)

= Normalized influence of criterion based on AHP.

= Estimated weights of criterion.

= Sum of estimated weights for all criterions.

= Indicate the share of criterion in total influence (100%) of criterion which can be distributed within the criterion according to estimated weights 27.


3.3.3. Normalized Influences

The influences of criterion interpret the share of individual criteria in formations agriculture development (100%) and vary according to sub-watersheds 27, 28. Here, sub-watershed wise influences of criterion were normalized according to spatial distribution in sub-watersheds (equation 2) 27.

(2)

= Watershed wise normalized development influence.

= Cell value of criterion for the watershed

= Sum of cell values of criterion.

= Estimated development influence of criterion based on AHP.


3.3.4. Weighted Development

Sugarcane, vegetables, Grains and Fruits have been widely used by several scholars for agriculture development. These crops can be useful to decide the economic level of development and useful for overall agriculture development of sub-watersheds 29 using normalized pairwise comparison matrix 21, calculated influences (Table 9) for criterion and watershed wise normalized influences 27.

(3)

= Agriculture development of watershed

= Watershed wise normalized influence.

= Number of criterion

= Criterion

4. Results

Influences of sub-watersheds for agriculture development were calculated using multi-criteria based AHP method of criterions. Sugarcane, vegetables, pulses, fruits, rice and grains criterions (6) were selected and ranked using expert opinion for estimations of weights and influences. Estimated influences of six criterions were normalized based on spatial distribution in selected sub-watersheds for agriculture development in 2016 and 2019. Estimated agriculture development was classified into three classes: high, moderate, and low development (Figure 8).

4.1. Highly Development

In 2016, 19 (13.57%) and 2019, 13 (9.29%) sub-watersheds are classified into the class ‘Highly development’ (1.56<) for agriculture development (Figure 8). These watersheds show near bank of river, in this area, the river flows down the hilly region, which reduces the slope, moderate rainfall, accumulated soil and availability of irrigation have led to agricultural development. These watersheds are located in gentle slope with moderate rainfall. The productivity of these soils is high and natural resources are respectable for agriculture development. Population the region is belongs to economically good category. These watersheds show low migrations for their livelihood. Therefore, these sub-watersheds should be considered for agricultural development with high class.

4.2. Moderate Development

In 2016 and 2019 sub-watersheds 49 and 55 (Table 10) respectively classified into the class, ‘Moderate development’ show Gentle slopes (27.80% area), and calcareous soils with moderate erosion observed in these watersheds. Moderate surface erodibility and runoff for less rainfall, drought is common phenomenon in the region and population occasionally migrating for livelihood to irrigated and urban areas. Therefore, these sub watersheds also show moderate agriculture development in the region.

4.3. Less Development

About 51.43% in 2016 and 2019 sub-watersheds (Table 10) in the basin classified in ‘low development’ with low rainfall, low irrigation, unduly surface, low erosion activities and comparatively low agriculture. These watersheds are located far away to the Major River and dams with low groundwater potentials in rainy season. Therefore, these sub watersheds also show low agriculture development.

5. Conclusions

1. AHP based multi-criteria analysis with normalized influences of criterion is useful for agriculture development.

2. Criterion 6 i.e. Sugarcane, vegetables, pulses, fruits, rice and grains criterions were used for prioritization of agriculture development.

3. Expert opinion use for ranks of criterion

4. Weights estimated using AHP methods were used for calculations of influences of criterion. Further, calculated influences were normalized based on spatial distribution of selected criterion.

5. Sub-watersheds in the basin were classified into high, moderate and low agriculture development priorities.

6. Distribution of rainfall, soils, slope and irrigation show importance in agriculture development of sub-watersheds in study area.

7. The methodology used for present study can be useful tool for quick agriculture development of watersheds.

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Published with license by Science and Education Publishing, Copyright © 2021 Ravindra D. Gaikwad and Vijay S. Bhagat

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Ravindra D. Gaikwad, Vijay S. Bhagat. Using Multi - Criteria, AHP and Influence Approaches for Agriculture Development: A Case Study of Upper Mula Basin in Maharashtra (India). Applied Ecology and Environmental Sciences. Vol. 9, No. 3, 2021, pp 368-379. http://pubs.sciepub.com/aees/9/3/7
MLA Style
Gaikwad, Ravindra D., and Vijay S. Bhagat. "Using Multi - Criteria, AHP and Influence Approaches for Agriculture Development: A Case Study of Upper Mula Basin in Maharashtra (India)." Applied Ecology and Environmental Sciences 9.3 (2021): 368-379.
APA Style
Gaikwad, R. D. , & Bhagat, V. S. (2021). Using Multi - Criteria, AHP and Influence Approaches for Agriculture Development: A Case Study of Upper Mula Basin in Maharashtra (India). Applied Ecology and Environmental Sciences, 9(3), 368-379.
Chicago Style
Gaikwad, Ravindra D., and Vijay S. Bhagat. "Using Multi - Criteria, AHP and Influence Approaches for Agriculture Development: A Case Study of Upper Mula Basin in Maharashtra (India)." Applied Ecology and Environmental Sciences 9, no. 3 (2021): 368-379.
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