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Indian J. of Agroforestry Vol. 18 No. 1 : 58-62 (2016)
Challenges in agroforestry mapping for carbon sequestration through remote sensing and CO2 Fix model in Guna district R.H. Rizvi, Ram Newaj, Amit Kumar Jain*, O.P. Chaturvedi, Rajendra Prasad, Badre Alam, A.K. Handa, Chavan Sangram, Abhishek Maurya, P.S. Karmakar, A. Saxena and Gargi Gupta ICAR- Central Agroforestry Research Institute, Gwalior Road, Jhansi -284 003. U.P., India. *Corresponding authors Email:
[email protected] ABSTRACT: Global warming is becoming a huge problem for our mother earth due to carbon emission in the wake of modernization and urbanization. Carbon sequestration is a phenomenon for the storage of CO2 or other forms of carbon to mitigate global warming. Remote sensing becomes an effective tool for mapping and monitoring of agriculture, forestry and other earth features. Agroforestry mapping is an important parameter for developmental planning at regional and national level. The present study aims at estimating area and carbon sequestration potential under agroforestry in Guna district of Madhya Pradesh. RS-2/ LISS-III remote sensing data was used to identify agroforestry, forest/ non-forest land uses and land covers. It was estimated that about 3.55 percent of the district area under agroforestry. Dynamic CO2FIX model v3.1 was used to assess the baseline (2011) carbon and to estimate carbon sequestration potential (CSP) of agroforestry systems for a simulation period of 30 years in Guna district. The estimated numbers of trees existing on farmer’s field was 6.40 per hectare. The baseline standing biomass in the tree components was 3.99 Mg DM ha-1 and the total biomass (tree + crop) was 9.55 Mg DM ha-1 in the district. The CSP of existing agroforestry systems for simulation period of thirty years was estimated to the tune of 0.159 Mg C ha-1 yr-1. Key word: Agroforestry mapping, carbon sequestration, CO2FIX model, climate change and remote sensing. Received on: 04/05/2016
Accepted on: 09/06/2016
1. INTRODUCTION Carbon sequestration is a phenomenon for the storage of CO2 or other forms of carbon to mitigate global warming. Through biological, chemical or physical processes, CO 2 is captured from the atmosphere. Carbon sequestration is a way to mitigate the accumulation of greenhouse gases in the atmosphere released by the burning of fossil fuels and other anthropogenic activities. Agroforestry is a viable alternative to prevent and mitigate climate change. IPCC recognized agroforestry as having high potential for sequestering carbon under the climate change mitigations strategies (Watson et al., 2000). Many studies have reported the carbon sequestration potential (CSP) of forest and agroforestry in India (Dhyani et al., 1996; Ravindranath et al., 1997; Haripriya 2001; Lal and Singh 2000; Swamy et al., 2003; Swamy and Puri 2005; Ajit et al., 2013). In India, an average sequestration potential in agroforestry has been estimated to be 25 Mg C ha-1 over 96 million ha (Sathaye and Ravindranath, 1998), but there is a considerable variation in different regions depending upon the
biomass production Newaj and Dhyani, 2008; Dhyani et al., 2009) and method of estimation. Most of the estimates are based on biomass productivity and do not take into account contributions such as soil and others. This is mainly due to absence of a standard methodology for carbon sequestration potential in Indian context. Land use refers to the way in which land has been used by humans and their habitats, usually with accent on the functional role of land for economic activities. Land cover refers to the physical characteristics of earth’s surface, natural vegetation, water bodies, soil/rock, artificial cover and others resulting due to land transformation. In India, agroforestry area through remote sensing and preliminary estimates were attempted by Rizvi et al., (2014, 2013). Ahmad et al., (2007) developed a model for prediction of area under agroforestry in Yamunanagar district of Haryana State. Statistical evaluation and identification of villages that have potential for agroforestry was done by Ahmad et al., (2010) using GIS. Remote Sensing has become an effective tool for mapping and monitoring of agriculture, forestry and other
Pankaj\E:\DATA-2014\NRC for Agroforestry, Jhansi\IJAF 18 (1), 2016 Formated articles—MS 10-770
Challenges in agroforestry mapping for carbon sequestration through remote sensing and CO2 Fix model
earth features. A strategy of forest/ non-forest cover mapping based on remotely sensed data and GIS was demonstrated by Maurya et al., (2013). Remote sensing technique has been used f or crop forecasting (Chaudhary, 1999), crop inventory (Salman and Saha, 1998), estimation of acreage and crop production (Maurya, 2011), Calculating carbon sequestration (Tripathi et al., 2010). With the advent of remote sensing, future planning and management of natural resources has considerably broadened. The objective of the study was to estimate area under agroforestry using GIS & remote sensing and also carbon sequestration potential of agroforestry systems in Guna district of Madhya Pradesh. 2. MATERIALS AND METHODS Study Area Guna the gateway of Malwa and Chambal is located on the northern-eastern part of Malwa Platue between river Parbati and Betwa. The District is situated between latitude 23053" N and 2506’55" N and longitude 76048’ 30"E and 780 16’70"E (Fig. 1). The western boundary of the district is well defined by the river. Field Survey In the present investigation stratified random sampling was used and two block and from each block two villages were randomly selected. The primary data on tree species, their number, diameter at breast height (DBH), crops grown with trees was collected from farmers’ field. The available tree species were then grouped into three categories viz. slow, medium and fast growing tree. Methodology For mapping agroforestry area in Guna district, Resourcesat-2/ LISS III remote sensing data (spatial resolution 23.5 m) was used for land use/ land cover (LULC) classification. These data (97/54, 14-Oct-2013 and 97/55, 12-Mar-2013) were visually and digitally interpreted using ERDAS 2011 and ArcGIS 9.3 software. Classification accuracy was obtained with the help of 100 GPS points collected from farmers’ fields on agroforestry and thematic maps were finalized. Maximum likelihood method of supervised classification was applied for assessment of land uses and land covers of study districts.
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The dynamic carbon accounting model CO2FIX v3.1 (Masera et al., 2003; Schelhaas et al., 2004) was used to assess the baseline carbon and simulating the carbon sequestration potential (CSP) of agroforestry systems (AFS) in the district. CO2FIX model has been developed as part of the CASFOR II project. It is a user-friendly tool f or dynamically estim ating the carbon sequestration potential of forest management, agroforestry and afforestation projects. This model consists of six modules viz biomass module, soil module, products module, bioenergy module, financial module and carbon accounting module. For the purpose of simulating carbon stocks under agrof orestry systems, the modules taken into considerations are biomass, soil and carbon accounting modules. CO2FIX model requires primary as well as secondary data on tree and crop components (called ‘cohorts’ in CO2FIX terminology) for preparing the account of carbon sequestered under agroforestry systems on per hectare basis. The primary data includes tree species existing on farmlands and their number, DBH, crops grown by farmers on farmlands along with their productivity, area coverage etc. Whereas the secondary data includes the growth rates of tree biomass components (stem, branch, foliage, root) for various species on annual basis. 3. RESULTS AND DISCUSSION Guna district was classified into ten LULC classes viz. agroforestry, cropland, plantation, forest, degraded forest, wasteland, grassland, water bodies, built-ups, and sandy area. With the help of remote sensing/ GIS technology, the estimated agroforestry area of Guna district is 3.55 percent (Table 1 and Figure 1). Table 1.Land use and land cover statistics of Guna district LULC Classes Agroforestry Cropland Plantation Forest Degraded forest Grassland Wasteland Sand Waterbody Builups Total
Area (ha) 21783.1 374158 2982.76 42434.2 121736 3061.12 31489 1971.48 12852.6 2004.17 614472.43
Area (%) 3.55 60.89 0.49 6.91 19.81 0.50 5.12 0.32 2.09 0.33 100
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Indian J. of Agroforestry Vol. 18 No. 1 : 58-62 (2016)
Fig. 1. Location and LULC map of Guna district
Challenges in agroforestry mapping for carbon sequestration through remote sensing and CO2 Fix model
Table 2.Number of trees per hectare for different categories Cohorts
Average number of trees per hectare Estimated age of existing trees (years)
Slow growing 1.39 40.3
Tress category Medium Fast growing growing 3.80 1.20 17.22
9.65
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site’s climate factors viz monthly average temperature, total precipitation along with its distribution over different months, evapotranspiration etc. Similar results have been reported by Singh et al. (2011) that agricultural soils of Indo-Gangetic plains, on an average, contain 12.4 to 22.6 Mg ha-1 of organic carbon in the top 1 m soil depths. Lal (2004) reported that SOC concentration increased with increased rainfall in several Indian soils.
Table 3.Biomass accumulated and carbon sequestrated under agroforestry system in Guna Tree Biomass (above and below ground ) Mg DM ha
-1
Baseline Simulated -1 Total Biomass (tree+ crop) Mg DM ha Baseline Simulated -1 Soil carbon (Mg C ha ) Baseline Simulated -1 Biomass carbon (Mg C ha ) Baseline Simulated -1 Total carbon (biomass + soil) (Mg C ha ) Baseline Simulated -1 Net carbon sequestered in agroforestry systems over the simulated period of thirty years (Mg C ha ) -1 -1 Estimated annual carbon sequestration potential of agroforestry system (Mg C ha yr )
Biomass
Carbon
Carbon sequestered
3.99 10.67 9.55 16.45 23.38 24.80 4.31 7.59 27.61 32.39 4.78 0.159
Average numbers of trees per hectare were 1.39, 3.80 and 1.20 in slow, medium and fast growing groups respectively and clubbing to a total of 6.40 trees ha-1 in Guna. The average age of the existing trees was 40, 17 and 9 years respectively for slow, medium and fast growing trees (Table 2). The secondary data on district wise crop productivity was obtained from NIC (National Informatics Centre, Ministry of Communications and Information Technology, Govt. of India, New Delhi) and the respective District Statistical Offices. The secondary data includes production, productivity and average yield of district along with land use pattern.
4. CONCLUSION
The tree biomass (above and below ground) increased from 3.99 to 10.67 Mg DM ha-1. The soil carbon for Guna district is expected to increase from 23.38 to 24.80 Mg C ha-1 for thirty year simulation. Biomass carbon and total carbon has been estimated to be 4.31 and 27.61 Mg C ha-1 for baseline. This has become 7.59 and 32.39 Mg C ha-1 for simulated period of 30 years. Net carbon sequestered was estimated to be 4.78 Mg C ha-1 in 30 years period. In this way, carbon sequestered at district level would be 0.104 million tC. The CSP of existing agroforestry system was estimated to 0.159 Mg C ha1 -1 yr in Guna (Table 3).
Authors are thankful to ICAR for funding NICRA project and authors are also thankful to the Director, CAFRI, Jhansi for providing all kind of support for this project.
The CSP increased with increasing tree density (number of tree per hectare). The CSP was influenced by the
Agroforestry systems whether traditional or commercial plays have potential of carbon sequestration in the form of tree biomass and soil carbon. They play a vital role in mitigating the effects of climate change through sequestration of atmospheric CO2. CO2FIX model in conjunction with geospatial technology can be successfully applied for accurate estimation of area and carbon sequestration under agroforestry at district or region level. ACKNOWLEDGEMENT
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