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Int.J.Curr.Microbiol.App.Sci (2018) 7(3): 1377-1386 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 03 (2018) Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2018.703.165 Dynamics of Water Productivity under Agriculture and Agroforestry Land Use System in Jabalpur, Madhya Pradesh, India Yogesh Kumar1* and M.L. Sahu2 1 Department of Environmental Science, Indira Gandhi National Tribal University (IGNTU), Amarkantak, Madhya Pradesh, India 2 Department of Forestry, JNKVV, JABALPUR, India *Corresponding author ABSTRACT Keywords Dynamics, Water productivity, Turmeric equivalent Agroforestry Article Info Accepted: 12 February 2018 Available Online: 10 March 2018 The present study was carried out to determine the dynamics of water productivity under agriculture and agroforestry land use system in Jabalpur region of Madhya Pradesh. The statistical analysis was carried out in spilt plot design, there were two treatments and three sub treatments were taken. The main treatment was farming practices that was agroforestry and agriculture where sub treatment was different date of showing. All the product of agroforestry and agriculture were converted in to turmeric equivalent yield, total turmeric equivalent yield and Turmeric Equivalent Water Productivity (TEWP). All of these yields were used to determine water productivity. The water productivity of agroforestry was (321 kg ha1 cm-1) while in agriculture it was 90 kg ha-1cm-1 Introduction In the light of globalization, population growth and climate change, water resources management is increasingly becoming a major sustainability challenge, especially for arid and semi-arid regions. It is widely acknowledged that water scarcity or insecurity is not only subject to physical factors and constraints, but also due to poor management of available water resources (Molden et al., 2007). Water consumption has increased fourfold in the last 100 years. Population facing water scarcity increased from 0.24 billion people (14 percent of the global population 100 years ago) to 3.8 billion (58 percent of today’s population) (Kummu et al., 2016). Most population growth is taking place in developing countries, where water is scarce and characterized by rainfall variability, intermittent dry spells, recurrent drought years and high evaporative demand (Rockstrom et al., 2007). Population share of India in world accounts as 17%, whereas fresh water share is only 4% of the total water resources across the globe. Total eradication of hunger in India requires around 1,860 km3/yr of water by 2030 and more than 2,000 km3/yr by 2050. 1377 Int.J.Curr.Microbiol.App.Sci (2018) 7(3): 1377-1386 Respective increases is 160 & 180 percent compared to the current consumption of water. (SEI, 2005). Unlike water use in the domestic and industrial sectors, there is significant lack of information in most countries regarding agricultural water use, as irrigation abstractions from rivers, dams and aquifers (i.e. blue water), are rarely fully metered and charged (Easter and Liu, 2005). The economic value of water in agriculture is much lower than that in other sectors (Barker et al., 2003). Many researcher across the globe found that, in developing countries, large amount of water applied to crop field for increasing the agriculture production, is lost as nonproductive evaporation (Rockstrom et al., 2007). According to FAO Agriculture is the main user of the water; 88 percent of all the water withdrawn is used for irrigation (FAO, 2017). Together, the increasing food demand and decreasing water allocation suggest that the agriculture sector has to produce more food with less water (Cai and Sharma 2010). However, the conventional methods of cropping and badly managed resources are not able to fulfill it. There is need of certain measures/technology like water productivity which aimed at reducing water losses systems (FAO, 2012). Definition of water productivity is scale dependent. It can be analyzed at the plant level, field level, farm level, system level and basin level, and its value would change with the changing scale of analysis (Molden et al., 2003). Its unit is kg m-3or kg ha-1 cm-1 (1kg m-3=100 kg ha-1 cm-1). Land use system like agroforestry offers promising option for efficient and sustainable use of land and water. Water conservation and more productive use of water is one of the key benefits of agroforestry. Determination of water productivity is much common in agriculture, but it is rare in agroforestry, with special reference to India. Keeping the above facts in view, the present study was carried out analyze the dynamics of water productivity in Agriculture and Agroforestry system of crop cultivation. Materials and Methods The details of material used and the methods adopted during the course of study Dynamics of water productivity under agriculture and agroforestry land use system in Jabalpur, Madhya Pradesh, India Study area The field experiment was conducted at Dusty Acre Research Farm, Department of Forestry, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur (M.P.). The present investigation was carried out during 2014-2015. Location and extent Study area lies at 23o12’50” North latitude & 79o57’56” East longitude. Study area belongs to Kymore Plateau and Satpura Hills Agroclimatic Zone as per classification of National Agricultural Research Project. Recently, this area has been classified as agro-ecological sub-region number 10.1 (Vindhyan Scarplands, Bundelkhand, and Narmada Valley, hot dry sub-humid ecological sub region with medium deep black soil). Topography The topography of the area plain to gently sloping. Slope of the land vary from 0 to 1%. Climate Study area enjoys a typical subtropical climate with hot dry summer and cool dry winter. Temperature extremes vary between minimum temperature of 20c in December-January months to maximum temperature of 460c in May–June months. Based on 20 years mean meteorological data, the average annual 1378 Int.J.Curr.Microbiol.App.Sci (2018) 7(3): 1377-1386 rainfall of the locality is 1350 mm, which mostly received between mid-June to end of September with an occasional winter showers during December and January months. The mean monthly minimum temperature varies between 5.3 to 6.1in December and January, and maximum temperature varies between 40 to 42°C during May and June, respectively January is the coldest month of the year with minimum temperature being 5°C. Generally relative humidity remains very low during summer (20 to 23%); moderate (60 to 75%) during winter and it attains high value (80 to 95%) during rainy season. Weather conditions during the crop season Seasonal variations prevailing during the growth period play an important role on the growth and development of turmeric crop as well as Dalbergia sissoo trees, which ultimately influenced the final yield of crops. The weekly meteorological data during the course of investigation recorded at Meteorological Observatory, Agricultural Engineering College, JNKVV, Jabalpur are presented in Table 1. It is evident from the data that weather condition was almost favourable for the growth and development of turmeric as well as shisham tree. The monsoon was commenced in the third week of June and terminated in the last week of September (Table 1). During the growing season (June 2014 to April 2015) maximum temperature (39.8) was recorded in the month of June and minimum (20.5) in the month of January. The average relative humidity was 44 to 96% in the morning and 17 to 88% in the evening. The rainfall during the crop season was 1460.8 mm and was received in 71 rainy days which had a beneficial effect on growth and development of turmeric crop as well as for the Shisham tree. Soil As earlier mentioned the present investigation was the third consecutive year of experimentation at the same site. Hence, data pertaining to initial soil status of various physical-chemical properties were recorded from the soil sample taken at the time of turmeric planting from 10 places up to a depth of 0-30 cm with the help of screw type soil auger. The soil samples were well mixed together for making representative samples. The composite samples were analyzed for physico-chemical properties of the soil in the laboratory, Department of Soil Science and Agricultural Chemistry as per standard methods. The analytical values are presented in Table 2. To know the changes in chemical properties of the soil after three year of experimentation, soil samples from each plot were also taken and analyzed separately Physico-chemical properties of the soil of the experimental field It is obvious from the results that the soil of the experimental field was sandy clay loamy in texture, neutral in reaction (pH 7.21) with medium organic carbon content and having low electrical conductivity and medium in available nitrogen (N) and phosphorus (P) and low in available potash (K) content. Experimental details To determine the water productivity of crop + Tree (Agroforestry) Main treatment: 2 Agroforestry Silviculture 1379 Int.J.Curr.Microbiol.App.Sci (2018) 7(3): 1377-1386 Sub treatment: 4 To compare the water productivity of Agroforestry and Agriculture In case of agroforestry, the total output will be rhizome, large-sized timber, small-sized timber and fuel wood. Note Main treatment: 2 Sub treatment: 3 All output other than rhizome was converted into turmeric equivalent yield considering market rates of produce. The market price of different derived output under different practices was as follows: Observations recorded Rhizome = Rs 55 kg-1 Meteorological parameters Large-sized timber (diameter above 10 cm) = Rs 17600 m-3 Agroforestry Agriculture Daily Rainfall data Daily Pan-evaporation Soil physical parameters Small-sized timber (diameter 10cm to 7 cm) =Rs 10600 m-3 Fuel wood = Rs 5 kg-1 Soil texture Water used Tree growth parameters Diameter at breast height It includes the effective rainfall plus irrigation for agroforestry and agriculture and only rainfall for silviculture. Crop parameters Effective rainfall Rhizome yield By considering daily rainfall data, mean monthly pan-evaporation, soil properties the effective rainfall has been derived from Potential Evapotranspiration /Precipitation Ratio Method (India) (FAO, 1974) Methodology to determine crop water productivity The crop water productivity was worked out by dividing the Turmeric equivalent yield by total water used. Physical water Productivity (kg ha-1 cm-1) = (Total yield (kg ha-1)/Total water used (cm)) Total yield In case of agriculture, the total output will be rhizome yield Irrigation Water is supplied to all portions of field by pipe irrigation method. Irrigation water was calculated using pump discharge rate, time of irrigation and number of irrigation to a particular crop. The discharge rate was measured with a 40 liter drum and stop watch. This measurement was taken 3 times in a field and its means was considered for the calculation purpose. 1380 Int.J.Curr.Microbiol.App.Sci (2018) 7(3): 1377-1386 IR (Irrigation water) = Pump discharge rate x time of irrigation x No. of Irrigation The depth of irrigation was calculated by dividing the amount of irrigation with plot area. calculated using the derived local volume table of Jabalpur region. The different regression models used were as follow; For large-sized timber estimation Pruning intensities √v = 0.056448 + 0.01583D P0 √v = - 0.26159 + 0.03088D P25 √v = - 0.121356 + 0.02594D P50 √v = - 0.14682 + 0.02878D P75 Observations recorded Daily rainfall data The daily rainfall data during the course of investigation recorded during crop season at Meteorological observatory, College of Agricultural Engineering, JNKVV, Jabalpur. Daily pan-evaporation data For small-timber estimation √v = 0.02815 + 0.00594D P0 √v = - 0.06572 + 0.00919D P25 √v = - 0.01037 + 0.00684D P50 √v = - 0.14423 + 0.01367D P75 Daily pan-evaporation data was recorded at Meteorological observatory, College of Agricultural Engineering, JNKVV, Jabalpur. For fuel-wood estimation Diameter measurement of D. sissoo √w = 2.84865 + 0.11694D P0 √w = - 1.84900 + 0.31852D P25 √w = - 0.24751 + 0.20303D P50 √w = - 1.36957 + 0.24582D P75 Diameter of trees was measured with the help of calliper. Two diameter for each tree were taken perpendicularly and average was taken out as mean diameter. Where, v = Volume (m3) w= Weight (kg) D = Diameter at breast height (cm) Rhizome yield (Kg ha-1) After harvesting and cleaning the rhizome from each net plot, it was weighed on a double pan balance. The rhizome yield per hectare was obtained by multiplying the net plot yield by the converting factor {10,000 dividing by net area (m2) of plot}. The yield was expressed in kilograms per hectare. Volume of large-sized (diameter above 10 cm), small-sized timber (diameter 10cm to 7 cm) and weight of fuelwood (diameter 7 cm to 4 cm) The volume of timber and weight of fuel wood under different pruning intensities were Statistical analysis The data calculated from the experiment were tabulated and analyzed statistically by method of analysis of variance as suggested by Cochran and Cox (1950). The significance of the treatment mean square at 5 percent level was tested with 'F' test. When 'F' test showed the significance of treatment using the significance of critical differences at 5 per cent level further tested the differences between the treatment means. 1381 Int.J.Curr.Microbiol.App.Sci (2018) 7(3): 1377-1386 Table.1 Weekly meteorological parameters during the crop season (June2014 to March 2015) Month June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. March Meteo . Week 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 1 2 3 4 5 6 7 8 9 10 11 12 13 Temperature Max. 39.8 35.6 36.5 34.5 31.3 32.3 28.2 26.3 27.7 28.2 30.2 31.9 30.8 30.7 30.8 31.9 33.4 32.4 32.5 31.6 27.9 28.2 28.6 27.9 28.4 28.7 29 25.3 23.8 20.5 22.1 22.2 21.6 22.5 24.2 26.8 30.6 26.7 28 26.8 31.8 35.4 Min. 26.4 25.6 26.4 26.1 25.6 24.5 23.3 24.6 23.7 24 25.1 24.2 23.7 23.4 23.5 21.6 21 20.4 18.8 16.6 14.4 13.9 14.4 8.9 10.2 8 11.8 5.6 4.8 11.7 5.3 5.3 12.1 8.7 10.2 10.4 12 14.5 12 15.2 13.8 19 Relative Humidity% Morning Evening 64 37 74 52 65 38 71 41 79 59 90 79 91 79 92 79 86 73 86 63 83 58 88 65 91 71 91 72 89 55 85 41 86 53 88 55 91 44 89 41 87 29 87 29 83 26 82 20 85 24 88 24 89 52 86 32 87 32 90 61 87 38 91 37 89 75 85 44 88 52 88 40 86 33 85 54 85 39 87 54 80 26 55 23 1382 SunShine hrs 6.2 7 4.5 6.5 5.9 3.2 3.4 2.3 4.9 5 6.7 7.8 2.4 3.8 8.5 10 9.4 8.4 7.9 8.8 8.6 8.2 6 8.6 8.6 8.7 6.2 7.6 8.5 6.5 8.5 8.3 3.7 9.8 7.1 9.1 9.7 6.8 9.5 6..0 10.3 9.5 Rainfall (mm) 37 72.6 9.8 296.8 116 117.5 119.9 32.4 145.8 101.8 84.4 3 52.2 87.4 11 0 2.3 0 0 0 0 0 0 0 0 0 3.2 0 0 37.7 0 0 10.2 10.8 14.4 6.2 0 64.8 0 23.6 0 0 No of Rainy days 3 4 1 3 4 6 3 5 5 2 0 2 7 6 1 0 1 2 0 0 0 0 0 0 0 0 1 0 0 3 0 0 2 2 1 1 0 3 0 3 0 0 Wind vel. (Km/hr) 7 7.9 6.5 7.4 7.1 5.8 5.5 5.4 7.9 6.1 3.1 4.1 4.1 4.8 4.2 2.5 2.3 4.7 2.3 1.7 1.6 2.6 2.5 1.8 2.1 2.5 2.6 2.2 2.1 3.8 2.1 2.6 3.3 2.7 4.5 2.8 1.9 3.2 2.9 3.6 2.2 5.3 Int.J.Curr.Microbiol.App.Sci (2018) 7(3): 1377-1386 Table.2 To compare the water productivity of Agroforestry and Agriculture Source of variation Replication Main treatment (Farming Practice) Error A Sub-treatment (Date of sowing) Interaction Error B Total d. f S.S M.S.S F cal 3 1 3 2 2 12 23 F tab at 5% at 1% 10.13 34.12 3.88 3.88 6.93 6.93 Skeleton for analysis of variance (ANOVA) Table.3 Turmeric yield of agroforestry and agriculture (kg ha-1) Practices Agroforestry Agriculture SEm± CD at 5% CD at 1% Average 2926 6170 1540 4900 8996 Table.4 Turmeric yield in different date of sowing (kg ha-1) Date of sowing Yield 4805 4377 4463 514 1120 1571 D1 D2 D3 SEm± CD at 5% CD at 1% Table.5 Turmeric equivalent yield of agroforestry and agriculture (kg ha-1) Practices Yield 21985 6170 2152 6847 12568 Agroforestry agriculture SEm± CD at 5% CD at 1% 1383 Int.J.Curr.Microbiol.App.Sci (2018) 7(3): 1377-1386 Table.6 Total TEY in different date of sowing (kg ha-1) Date of sowing D1 (20-06-2014) D2 (27-06-2014) D3 (05-07-2014) SEm± CD at 5% CD at 1% Yield 15938 13149 13145 892 1943 2725 Table.7 Turmeric equivalent water productivity (TEWP) of agroforestry and Agriculture (kg ha-1 cm-1) TEWP (kg ha-1 cm-1) 321 90 31 100 183 Practices Agroforestry Agriculture SEm± CD at 5% CD at 1% Table.8 Turmeric equivalent water productivity in different date of sowing (kg ha-1 cm-1) TEWP (kg ha-1 cm-1) 233 192 192 13 28 40 Date of sowing D1 D2 D3 SEm± CD at 5% CD at 1% Results and Discussion Turmeric yield agriculture The findings of present study were analyzed and found the following details as follow Three sowing dates for turmeric were viz., 206-2014 (D1), 27-6-2014 (D2) and 05-07-2014 (D3). TEWP of these three sowing date are evaluated. The output of agroforestry is turmeric LST, SST and FW whereas output of agriculture is turmeric only. The LST, SST and FW were converted in to TEY in agroforestry of agroforestry and As shown in Table 3. The mean yield of agroforestry is 2926 kg ha-1, whereas it is 6170 kg ha-1 in Agriculture system As shown in Table 4 the turmeric yield in different dates of sowing are at par with each other. Turmeric yield in D1 (4805 kg ha-1), D2 (4377 kg ha-1) and D3 (4463 kg ha-1) were recorded. 1384 Int.J.Curr.Microbiol.App.Sci (2018) 7(3): 1377-1386 Total Turmeric equivalent agroforestry and agriculture yields in All products of agroforestry viz., LST, SST, FW and turmeric yield were converted in to TEY and added to get total TEY of agroforestry. It was analysed with TEY of agriculture. Total turmeric equivalent yield of agroforestry (21985 kg ha-1) was significantly superior to agriculture (6170 kg ha-1) (Table 3). As shown in Table 4 Total TEY in D1 (15938 kg ha-1) is significantly superior to, D2 (13149 kg ha-1) and D3 (13145 kg ha-1). D2 and D3 are at par. These total turmeric equivalent yield (TEY) were considered for determining the water productivity of different treatments. Water productivity in agroforestry and agriculture (kg ha-1 cm-1) To determine the turmeric equivalent water productivity (TEWP), total TEY of different treatment were divided by the water used in respective treatments. Water used in agroforestry treatment and agriculture treatment was 68.5cm.TEWP of agroforestry (321 kg ha-1 cm-1) was significantly superior with the agriculture (90 kg ha-1 cm-1). Table 7. The TEWP of D1 (233kg ha-1 cm-1) was significantly superior to D2 (192kg ha-1 cm-1) and D3 (192kg ha-1 cm-1). Table 8 TEWP of different farming practices As per Table 7 reveals that TEWP of agroforestry (321kg ha-1 cm-1) is significantly superior than TEWP of agriculture (90kg ha-1 cm-1). It is clear from that significantly lower TEWP was recorded in agriculture (90kg ha-1 cm-1) and the TEWP of agroforestry was (321kg ha-1 cm-1) In view of turmeric equivalent water productivity TEWP, agriculture farming practice (90 kg ha-1cm-1) as inferior among selected farming practices though agriculture utilized the same quantity of water (68.5 cm) like agroforestry, but yielded only 90 kg ha1 cm-1 TEWP, whereas agroforestry have 321 kg ha-1cm-1 TEWP. If the Moto of farming is “more biomass per drop of water” then agriculture farming fails in achieving this Moto. The agroforestry (321 kg ha-1cm-1) can choose best farming practice on the basis of water availability and demand of biomass. If sufficient water is available then go for agroforestry practice which gives more biomass and compare to agriculture. References Barker R, David D and Arlene I. 2003. 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Falkenmark, Assessing the water challenge of a new green revolution in developing countries, Proc. Natl. Acad. Sci. 104 (15) (2007) 6253–6260. SEI. 2005. Sustainable pathways to attain the Millenium Development Goals: Assessing the key role of water, energy and sanitation. 104pp. How to cite this article: Yogesh Kumar and Sahu, M.L. 2018. Dynamics of Water Productivity under Agriculture and Agroforestry Land Use System in Jabalpur, Madhya Pradesh, India. Int.J.Curr.Microbiol.App.Sci. 7(03): 1377-1386. doi: https://doi.org/10.20546/ijcmas.2018.703.165 1386