Suchergebnisse

Kosovo is a small and young state that gained an interim United Nations (UN)-administered status in the wake of the Dayton peace accord only in 1999; it declared independence in 2008. Compared to neighboring countries, it is still lacking in its basic infrastructure and its administrative and technical skills. In addition, with the onset of the War in Yugoslavia in 1992 most investment and normal maintenance came to a standstill. Much of the publicly owned infrastructure fell into disrepair or was vandalized, but private investments led to a construction boom which, however, is leading to many environmental problems. The government is committed to reconstruction and to the development of a peaceful state. It also intends to align with EU policies. Thus, the study has the specific objectives to: (i) assist the government to improve its river basin planning and management by providing (for demonstration purposes) a replicable tool and simulation model for integrated river basin planning and management; and (ii) support the government in its identification of priority measures of structural and non-structural nature to help strengthen the water resources sector performance. The source(s) for the financing of the identified projects will need to be identified further by the Government as the World Bank has not committed to involvement in the sector.

Not Available ; The land resource inventory of Padasavli-2 microwatershed was conducted using village cadastral maps and IRS satellite imagery on 1:7920 scale. The false colour composites of IRS imagery were interpreted for physiography and these physiographic delineations were used as base for mapping soils. The soils were studied in several transects and a soil map was prepared with phases of soil series as mapping units. Random checks were made all over the area outside the transects to confirm and validate the soil map unit boundries. The soil map shows the geographic distribution and extent, characterstics, classification and use potentials of the soils in the microwartershed. The present study covers an area of 667 ha in Aland taluk of Kalaburagi district, Karnataka. The climate is semiarid and categorized as drought prone with an average annual rainfall of 786 mm of which about 595 mm is received during south –west monsoon, 116mm during north-east and the remaining 75 mm during the rest of the year. An area of about 98 per cent is covered by soils, two per cent by waterbodies, settlements and others. The salient findings from the land resource inventory are summarized briefly below.  The soils belong to 6 soil series and 29 soil phases (management units) and 5 land management units.  The length of crop growing period is about 150 days starting from the 3rd week of June to 1st week of October.  From the master soil map, several interpretative and thematic maps like land capability, soil depth, surface soil texture, soil gravelliness, available water capacity, soil slope and soil erosion were generated.  Soil fertility status maps for macro and micronutrients were generated based on the surface soil samples collected at every 250 m grid interval.  Land suitability for growing major agricultural and horticultural crops were assessed and maps showing degree of suitability along with constraints were generated.  About 84 per cent area is suitable for agriculture and 14 per cent is not suitable for agriculture but well suited for forestry, pasture, agroforestry, silvi-pasture, recreation, installation of wind mills and as habitat for wildlife.  About 4 per cent of the soils are very deep (>150 cm), 9 per cent are moderately deep (75- 100 cm), 39 per cent are moderately shallow to shallow (25-75 cm) and about 46 per cent are very shallow (200 mm/m) in available water capacity, 9 per cent medium (100-150 mm/m) and about 85 per cent low (50-100 mm/m) and very low (9.0) and about 33 per cent slightly alkaline (pH 7.3-7.8) and 3 per cent has soils that are neutral (6.5-7.3) in reaction.  The Electrical Conductivity (EC) of the soils are dominantly 0.75%) and 17 per cent low (337 kg/ha) and 9 per cent low (20 ppm).  Available boron is low (0.6 ppm) in available iron.  Available manganese and copper are sufficient in all the soils.  About 78 per cent area has soils that are deficient (0.6 ppm) in available zinc.  The land suitability for 18 major crops grown in the microwatershed were assessed and the areas that are highly suitable (S1) and moderately suitable (S2) are given below. It is however to be noted that a given soil may be suitable for various crops but what specific crop to be grown may be decided by the farmer looking to his capacity to invest on various inputs, marketing infrastructure, price and finally the demand and supply position. Land suitability for various crops in the microwatershed Crop Suitability Area in ha (%) Crop Suitability Area in ha (%) Highly suitable (S1) Moderately suitable (S2) Highly suitable (S1) Moderately suitable (S2) Sorghum 61 (9) 40 (6) Sapota - - Maize - - Jackfruit - - Red gram - 101 (15) Jamun - 30(4) Sunflower 61(9) 27(4) Musambi 30(4) 58(9) Cotton 61 (9) 40 (6) Lime 30(4) 58(9) Sugarcane - - Cashew - - Soybean 61 (9) 40 (6) Custard apple 61 (9) 40 (6) Guava - - Amla 61 (9) 40 (6) Mango - - Tamarind - 30(4) Apart from the individual crop suitability, a proposed crop plan has been prepared for the 5 identified LMUs by considering only the highly and moderately suitable lands for different crops and cropping systems with food, fodder, fibre and horticulture crops that helps in maintaining the ecological balance in microwatershed  Maintaining soil-health is vital to crop production and conserve soil and land resource base for maintaining ecological balance and to mitigate climate change. For this, several ameliorative measures have been suggested to these problematic soils like saline/alkali, highly eroded, sandy soils etc.  Soil and water conservation treatment plan has been prepared that would help in identifying the sites to be treated and also the type of structures required.  As part of the greening programme, several tree species have been suggested to be planted in marginal and submarginal lands and also in the field bunds, hillocks, mounds and ridges SOCIO-ECONOMIC STATUS OF FARM HOUSEHOLDS Baseline socioeconomic characterisation is prerequisite to prepare action plan for program implementation and to assess the project performance before making any changes in the watershed development program. The baseline provides appropriate policy direction for enhancing productivity and sustainability in agriculture. Methodology: Padasavli-2 micro-watershed (Padasavli sub-watershed, Aland taluk, Gulbarga district) is located in between 17034'–17037' North latitudes and 76025'– 76028' East longitudes, covering an area of about 666.62 ha, bounded by Chincholi Khurd, Khanapur, Nagalogaon and Nirgudi villages with length of growing period (LGP) 120-150 days. We used soil resource map as basis for sampling farm households to test the hypothesis that soil quality influence crop selection, and conservation investment of farm households. The level of technology adoption and productivity gaps and livelihood patterns were analyses. The cost of soil degradation and ecosystem services were quantified. Results: The socio-economic outputs for Padasavli-2 micro-watershed (Padasavli subwatershed, Aland taluk, Gulbarga district) are presented here. Social Indicators  Male and female ratio is 58.7 to 41.3 per cent to the total sample population.  Younger age 18 to 50 years group of population is around 57.4 per cent to the total population.  Literacy population is around 97.8 per cent.  Social groups belong to others backward caste (OBC) is around 90.0 per cent.  Fire wood is the source of energy for a cooking among 90.0 per cent.  About 90.0 per cent of households have a yashaswini health card.  Dependence on ration cards for food grains through public distribution system is around 90.0 per cent.  Swach bharath program providing closed toilet facilities around 20.0 per cent of sample households.  Women participation in decisions making of agriculture production activities was found. Economic Indicators  The average land holding is 3.33 ha indicates that majority of farm households are belong to medium and large farmers. The total cultivated area by dry land condition among the sample farmers.  Agriculture is the main occupation among 23.9 per cent and agriculture is the main and agriculture labour is subsidiary occupation for 71.7 per cent of sample households. 2  The average value of domestic assets is around Rs.6300 per household. Mobile and television are popular media mass communication.  The average value of farm assets is around Rs. 4575 per household, about 60.0 per cent of sample farmers weeder and sprayer.  The average value of livestock is around Rs. 43000 per household; about 20.0 per cent of household are having livestock.  The average per capita food consumption is around 786.8 grams (1814.6 kilo calories) against national institute of nutrition (NIN) recommendation at 827 gram. Around 90.0 per cent of sample households are consuming less than the NIN recommendation.  The annual average income is around Rs. 47502 per household. About 60.0 per cent of farm households are below poverty line.  The per capita average monthly expenditure is around Rs.3280. Environmental Indicators-Ecosystem Services  The value of ecosystem service helps to support investment to decision on soil and water conservation and in promoting sustainable land use.  The onsite cost of different soil nutrients lost due to soil erosion is around Rs. 1364 per ha/year. The total cost of annual soil nutrients is around Rs. 893286 per year for the total area of 666.62 ha.  The average value of ecosystem service for food grain production is around Rs 14165/ ha/year. Per hectare food grains production services is maximum in sunflower (Rs. 15850) and redgram (Rs. 12479).  The data on water requirement for producing one quintal of grain is considered for estimating the total value of water required for crop production. The per hectare value of water used and value of water was maximum in redgram (Rs 496378) and sunflower (Rs 23903). Economic Land Evaluation  The major cropping pattern is redgram (90.3 %) and sunflower (9.7 %).  In Padsalvi-2 micro-watershed, major soils are margutti (MGT) series is having very shallow soil depth cover around 46.28 % of area. On this soil farmers are presently growing redgram (85.0 %), sunflower (15.0 %) and Mannur (MAN) are also having very deep soil depth cover 4.45 % of area, the crops are redgram.  The total cost of cultivation and benefit cost ratio (BCR) in study area of red gram range between Rs.21016/ha in MGT soil (with BCR of 1.64) and Rs.16175/ha in MAR soil (with BCR of 1.52).  In sunflower the cost of cultivation Rs. 16105/ha in MGT soil (with BCR of 1.98). 3  The land management practices reported by the farmers are crop rotation, tillage practices, fertilizer application and use of farm yard manure (FYM). Due to higher wages farmer are following labour saving strategies is not prating soil and water conservation measures. Less ownership of livestock limiting application of FYM.  It was observed soil quality influences on the type and intensity of land use. More fertilizer applications in deeper soil to maximize returns. Suggestions  Involving farmers is watershed planning helps in strengthing institutional participation.  The per capita food consumption and monthly income is very low. Diversifying income generation activities from crop and livestock production in order to reduce risk related to drought and market prices.  Majority of farmers reported that they are not getting timely support/extension services from the concerned development departments.  By strengthing agricultural extension for providing timely advice improved technology there is scope to increase in net income of farm households.  By adopting recommended package of practices by following the soil test fertiliser recommendation, there is scope to increase yield in redgram (19.3 to 56.4 %) and sunflower (46.0 %). ; Watershed Development Department, Government of Karnataka (World Bank Funded) Sujala –III Project

Not Available ; The land resource inventory of Padasavli-3 microwatershed was conducted using village cadastral maps and IRS satellite imagery on 1:7920 scale. The false colour composites of IRS imagery were interpreted for physiography and these physiographic delineations were used as base for mapping soils. The soils were studied in several transects and a soil map was prepared with phases of soil series as mapping units. Random checks were made all over the area outside the transects to confirm and validate the soil map unit boundries. The soil map shows the geographic distribution and extent, characterstics, classification and use potentials of the soils in the microwartershed. The present study covers an area of 690 ha in Padasavli-3 microwatershed in Aland taluk of Kalaburgi district, Karnataka. The climate is semiarid and categorized as drought prone with an average annual rainfall of 786 mm of which about 595 mm is received during south –west monsoon, 116 mm during north-east and the remaining 75 mm during the rest of the year. An area of about 99 per cent is covered by soils, one per cent by waterbodies, settlements and others. The salient findings from the land resource inventory are summarized briefly below.  The soils belong to 8 soil series and 29 soil phases (management units) and 5 land management units.  The length of crop growing period is about 150 days starting from the 3rd week of June to 1rd week of October.  From the master soil map, several interpretative and thematic maps like land capability, soil depth, surface soil texture, soil gravelliness, available water capacity, soil slope and soil erosion were generated.  Soil fertility status maps for macro and micronutrients were generated based on the surface soil samples collected at every 250 m grid interval.  Land suitability for growing major agricultural and horticultural crops were assessed and maps showing degree of suitability along with constraints were generated.  About 99 per cent area is suitable for agriculture.  About 18 per cent of the soils are very deep (>150 cm) to moderately deep (75-100 cm), 51 per cent are moderately shallow to shallow (25-75 cm) and about 30 per cent are very shallow (200mm/m) in available water capacity, 8 per cent medium (101-150 mm/m) and about 80 per cent low (50- 100 mm/m) and very low (0.75%) in organic carbon.  Major area of 99 per cent has soils that are low (337 kg/ha) in available potassium.  Available sulphur is low (20 ppm).  Available boron is low (0.6 ppm).  Available manganese and copper are sufficient in all the soils.  About 85 per cent area has soils that are deficient (0.6 ppm).  The land suitability for 18 major crops (agricultural and horticultural) grown in the microwatershed were assessed and the areas that are highly suitable (S1) and moderately suitable (S2) are given below. It is however to be noted that a given soil may be suitable for various crops but what specific crop to be grown may be decided by the farmer looking to his capacity to invest on various inputs, marketing infrastructure, price, and finally the demand and supply position. Land suitability for various crops in the microwatershed Crop Suitability Area in ha (%) Crop Suitability Area in ha (%) Highly suitable (S1) Moderately suitable (S2) Highly suitable (S1) Moderately suitable (S2) Sorghum 97 (14) 68 (10) Sapota - - Maize - - Jackfruit - - Red gram - 165 (24) Jamun - 75 (11) Sunflower 97 (14) 68 (10) Musambi 75 (11) 47(7) Cotton 97 (14) 68 (10) Lime 75(11) 47 (7) Sugarcane - - Cashew - - Soybean 97 (14) 68 (10) Custard apple 97 (14) 64(9) Guava - - Amla 97 (14) 64(9) Mango - - Tamarind - 75 (11) Apart from the individual crop suitability, a proposed crop plan has been prepared for the 5 identified LMUs by considering only the highly and moderately suitable lands for different crops and cropping systems with food, fodder, fibre and horticulture crops that helps in maintaining the ecological balance in the microwatershed.  Maintaining soil-health is vital to crop production and conserve soil and land resource base for maintaining ecological balance and to mitigate climate change. For this, several ameliorative measures have been suggested to these problematic soils like saline/alkali, highly eroded, sandy soils etc.  Soil and water conservation treatment plan has been prepared that would help in identifying the sites to be treated and also the type of structures required.  As part of the greening programme, several tree species have been suggested to be planted in marginal and submarginal lands and also in the field bunds, hillocks, mounds and ridges. SOCIO-ECONOMIC STATUS OF FARM HOUSEHOLDS Baseline socioeconomic characterisation is prerequisite to prepare action plan for program implementation and to assess the project performance before making any changes in the watershed development program. The baseline provides appropriate policy direction for enhancing productivity and sustainability in agriculture. Methodology: Padasavli-3 micro-watershed (Padasavli sub-watershed, Aland taluk, Gulbarga district) is located in between 17034'–17037' North latitudes and 76026'– 76029' East longitudes, covering an area of about 689.60 ha, bounded by Chincholi Khurd, Khandala, Khanapur and Nagalogaon villages with length of growing period (LGP) 120-150 days. We used soil resource map as basis for sampling farm households to test the hypothesis that soil quality influence crop selection, and conservation investment of farm households. The level of technology adoption and productivity gaps and livelihood patterns were analyses. The cost of soil degradation and ecosystem services were quantified. Results: The socio-economic outputs for the Padasavli-3 micro-watershed (Padasavli sub-watershed, Aland taluk, Gulbarga district) are presented here. Social Indicators  Male and female ratio is 45.2 to 54.8 per cent to the total sample population.  Younger age 18 to 50 years group of population is around 57.2 per cent to the total population.  Literacy population is around 81 per cent.  Social groups belong to other backward caste (OBC) is around 80 per cent.  Fire wood is the source of energy for a cooking among 60 per cent.  About 20 per cent of households have a yashaswini health card.  About 20 percent of farm households are having MGNREGA card for rural employment.  Dependence on ration cards for food grains through public distribution system is around 80 per cent.  Swach bharath program providing closed toilet facilities around 40 per cent of sample households.  Women participation in decisions making for agriculture production of households was found. Economic Indicators  The average land holding is 2.04 ha indicates that majority of farm households are belong to small and medium farmers. The dry land of 55.8 % and irrigated land 44.2% of total cultivated land area among the sample farmers. 2  Agriculture is the main occupation among 23.8 per cent and agriculture is the main and agriculture labour is subsidiary occupation for 66.7 per cent and private service is 9.5 per cent of sample households.  The average value of domestic assets is around Rs. 14798 per household. Mobile and television are popular media mass communication.  The average value of farm assets is around Rs. 106880 per household, about 50 per cent of sample farmers having bullock cart and plough.  The average value of livestock is around Rs. 23395 per household; about 40.0 per cent of household are having livestock.  The average per capita food consumption is around 915.2 grams (2067.73 kilo calories) against national institute of nutrition (NIN) recommendation at 827 gram. Around 10 per cent of sample households are consuming less than the NIN recommendation.  The annual average income is around Rs. 49807.6 per household. About 40.0 per cent of farm households are below poverty line.  The per capita average monthly expenditure is around Rs.1142. Environmental Indicators-Ecosystem Services  The value of ecosystem service helps to support investment to decision on soil and water conservation and in promoting sustainable land use.  The onsite cost of different soil nutrients lost due to soil erosion is around Rs. 983 per ha/year. The total cost of annual soil nutrients is around Rs. 674334 per year for the total area of 689.6 ha.  The average value of ecosystem service for food grain production is around Rs. 170920/ha/year. Per hectare food grain production services is maximum in red gram (Rs. 29175) and sugar cane (Rs. 19682).  The data on water requirement for producing one quintal of grain is considered for estimating the total value of water required for crop production. Per hectare value of water used and value of water was maximum in red gram (Rs. 544) and sugarcane (Rs.21). Economic Land Evaluation  The major cropping pattern is red gram (77.60 %) and sugarcane (22.4 %).  In Padasavli 3 microwatershed, major soil is Margutti (MGT) soil series is having very shallow soil depth cover around 28 % of area. On this soil farmers are presently growing red gram. Bhimanahalli (BHI) soil are also having shallow soil depth cover (20.13 %) of area, the major crop is red gram. Novinahala (NHA) soil series having shallow soil depth cover around 25.46 per cent of areas, crops are red gram (50 %) and sugarcane (50.0 %). Gutti (GTT) soil series having moderately shallow soil depth cover around 5 % of area; crop is red gram. Kamalapur soil 3 series having moderately deep soil depth cover around 7.41 per cent of areas; crop is red gram.  The total cost of cultivation and benefit cost ratio (BCR) in study area for redgram the cost of cultivation range between Rs 33406/ha in KMP soil (with of 1.85) and Rs.20087/ha in GTT soil (with BCR of 2.96).  In sugarcane cost of cultivation in NHA soil is Rs.52729/ha (with BCR of 1.37).  The land management practices reported by the farmers are crop rotation, tillage practices, fertilizer application and use of farm yard manure (FYM). Due to higher wages farmer are following labour saving strategies is not prating soil and water conservation measures. Less ownership of livestock limiting application of FYM.  It was observed soil quality influences on the type and intensity of land use. More fertilizer applications in deeper soils to maximize returns. Suggestions  Involving farmers is watershed planning helps in strengthing institutional participation.  The per capita food consumption and monthly income is very low. Diversifying income generation activities from crop and livestock production in order to reduce risk related to drought and market prices.  Majority of farmers reported that they are not getting timely support/extension services from the concerned development departments.  By strengthing agricultural extension for providing timely advice improved technology there is scope to increase in net income of farm households.  By adopting recommended package of practices by following the soil test fertiliser recommendation, there is scope to increase yield in red gram (11.1 to 7.1 %), sugarcane (73 %). ; Watershed Development Department, Government of Karnataka (World Bank Funded) Sujala –III Project

Not Available ; The land resource inventory of Kokkaragundi-3 Microwatershed was conducted using village cadastral maps and IRS satellite imagery on 1:7920 scale. The false colour composites of IRS imagery were interpreted for physiography and the physiographic delineations were used as base for mapping soils. The soils were studied in several transects and a soil map was prepared with phases of soil series as mapping units. Random checks were made all over the area outside the transects to confirm and validate the soil map unit boundaries. The soil map shows the geographic distribution and extent, characterstics, classification and use potentials of the soils in the microwartershed. The present study covers an area of 322 ha. in Kokkaragundi-3 microwatershed in Shirahatti taluk of Gadag district, Karnataka. The climate is semiarid and categorized as drought prone with an average annual rainfall of 633 mm.The north-east monsoon contributes about 165 mm and prevails from October to early December, maximum of 363 mm precipitation takes place during south–west monsoon period from June to September and the remaining 105 mm takes place during the rest of the year. An area of about 95 per cent is covered by soils, five per cent by waterbodies, settlements and others. The salient findings from the land resource inventory are summarized briefly below.  The soils belong to 15 soil series and 26 soil phases (management units) and 6land management units.  The length of crop growing period is about 150 days starting from the 3rd week of June to 3rd week of November.  From the master soil map, several interpretative and thematic maps like land capability, soil depth, surface soil texture, soil gravelliness, available water capacity, soil slope and soil erosion were generated.  Soil fertility status maps for macro and micronutrients were generated based on the surface soil samples collected at every 250 m grid interval.  Land suitability for growing major agricultural and horticultural crops were assessed and maps showing the degree of suitability along with constraints were generated.  About 95 per cent area is suitable for agriculture and 5 per cent is not suitable for agriculture but well suited for forestry, pasture, agro forestry, silvi-pasture, recreation, installation of wind mills and as habitat for wildlife.  About 39 per cent of the soils are very deep (>150 cm), deep (100 - 150 cm) to moderately deep (75 - 100 cm), 41per cent are moderately shallow to shallow (25-75 cm) and about 15 per cent are very shallow (200mm/m) in available water capacity, less than one per cent medium (100-150 mm/m) and about 56 per cent low (50-100 mm/m) and very low (9).  The Electrical Conductivity (EC) of the soils are dominantly 337 kg/ha) in available potassium.  Available sulphur is low (20 ppm).  Available boron is low (4.5 ppm).  Available manganese and copper are sufficient in all the soils.  Available zinc content is deficient (<0.6 ppm) in the entire microwatershed area  The land suitability for 21 major crops (agricultural and horticultural) grown in the microwatershed were assessed and the areas that are highly suitable (S1) and moderately suitable (S2) are given below. It is however to be noted that a given soil may be suitable for various crops but what specific crop to be grown may be decided by the farmer looking to his capacity to invest on various inputs, marketing infrastructure, price and finally the demand and supply position. Land suitability for various crops in the microwatershed Crop Suitability Area in ha (%) Crop Suitability Area in ha (%) Highly suitable (S1) Moderately suitable (S2) Highly suitable (S1) Moderately suitable (S2) Sorghum 75 (23) 82 (25) Jackfruit - 13 (4) Maize - 32 (10) Jamun - 124 (37) Bengal gram 69 (22) 132 (41) Musambi 56 (17) 68 (21) Ground nut - 140 (43) Lime 56 (17) 61 (19) Sunflower 67 (21) 101 (31) Cashew - - Cotton 50 (15) 140 (28) Custard apple 58 (17) 74 (24) Banana - 125 (39) Amla 56 (17) 71(22) Pomegranate - 125 (39) Tamarind - 113 (35) Mango - - Marigold - 150 (47) Guava - - Chrysanthamum 150 (47) Sapota - - Apart from the individual crop suitability, a proposed crop plan has been prepared for the 6 identified LMUs by considering only the highly and moderately suitable lands for different crops and cropping systems with food, fibre and horticulture crops that helps in maintaining the ecological balance in microwatershed  Maintaining soil-health is vital to crop production and conserve soil and land resource base for maintaining ecological balance and to mitigate climate change. For this, several ameliorative measures have been suggested to these problematic soils like saline/alkali, highly eroded, sandy soils etc.,  Soil and water conservation treatment plan has been prepared that would help in identifying the sites to be treated and also the type of structures required.  As part of the greening programme, several tree species have been suggested to be planted in marginal and sub-marginal lands and also in the hillocks, mounds and ridges. SOCIO-ECONOMIC STATUS OF FARM HOUSEHOLDS Baseline socioeconomic characterisation is prerequisite to prepare action plan for program implementation and to assess the project performance before making any changes in the watershed development program. The baseline provides appropriate policy direction for enhancing productivity and sustainability in agriculture. Methodology: Kokkaragundi-3 micro-watershed (Belhatti sub-watershed, Shirahatti taluk, Gadag district) is located in between 1501' – 1503' North latitudes and 75036' – 75038' East longitudes, covering an area of about 322 ha, bounded by Budihal, Belhatti, Hosur and Balehosur villages with length of growing period (LGP) 150-180 days. We used soil resource map as basis for sampling farm households to test the hypothesis that soil quality influence crop selection, and conservation investment of farm households. The level of technology adoption and productivity gaps and livelihood patterns were analyses. The cost of soil degradation and ecosystem services were quantified. Results: The socio-economic outputs for the Kokkaragundi-3 micro-watershed (Belhatti sub-watershed, Shirahatti taluk, Gadag district) are presented here. Social Indicators;  Male and female ratio is 52.2 to 47.8 per cent to the total sample population.  Younger age 18 to 50 years group of population is around 60.9 per cent to the total population.  Literacy population is around 84.8 per cent.  Social groups belong to scheduled caste (SC) is around 10 per cent.  Liquefied petroleum gas is the major source of energy for a cooking among 70 per cent.  About 50 per cent of households have a yashaswini health card.  Majority of farm households (70 %) are having MGNREGA card for rural employment.  Dependence on ration cards for food grains through public distribution system is around 90 per cent.  Swachha bharath program providing closed toilet facilities around 80 per cent of sample households.  Rural migration to unban centre for employment is prevalent among 4.3 per cent of farm households.  Women participation in decisions making is around among all the households were found. 2 Economic Indicators;  The average land holding is 1.56 ha indicates that majority of farm households are belong to small and medium farmers. The dry land of 83.9 % and irrigated land 16.1 % of total cultivated land area among the sample farmers.  Agriculture is the main occupation among 4.76 per cent and agriculture is the main and agriculture labour is subsidiary occupation for 83.33 per cent of sample households.  The average value of domestic assets is around Rs.13417 per household. Mobile and television are popular mass media communication.  The average value of farm assets is around Rs.137806 per household, about 40 per cent of sample farmers having plough and bullock cart.  The average value of livestock is around Rs.17208 per household; about 53 per cent of household are having livestock.  The average per capita food consumption is around 840 grams (1772.9 kilo calories) against national institute of nutrition (NIN) recommendation at 827 gram. Around 100 per cent of sample households are consuming less than the NIN recommendation.  The annual average income is around Rs.12100 per household. About 80 per cent of farm households are below poverty line.  The per capita monthly average expenditure is around Rs.1646. Environmental Indicators-Ecosystem Services;  The value of ecosystem service helps to support investment to decision on soil and water conservation and in promoting sustainable land use.  The onsite cost of different soil nutrients lost due to soil erosion is around Rs. 443 per ha/year. The total cost of annual soil nutrients is around Rs. 136065 per year for the total area of 322.24 ha.  The average value of ecosystem service for food grain production is around Rs 12662/ha/year in maize.  The average value of ecosystem service for fodder production is around Rs. 3337/ ha/year in maize.  The data on water requirement for producing one quintal of grain is considered for estimating the total value of water required for crop production. The per hectare value of water used and value of water was in maize (Rs. 27169). Economic Land Evaluation;  The major cropping pattern is maize (100 %).  In Kokkaragundi-3 micro-watershed, major soil is Kabulayathakatti (KLK) series is having very shallow soil depth cover around 15.28 % of area. On this soil farmers are presently growing maize, Attikatti (AKT) soils are also having shallow soil depth cover 0.44 %, Nabhapur (NBP) soil series having shallow 3 soil depth cover around 17.20 % of areas, Harve (HRV) soil series having shallow soil depth cover around 11.43 % of area, Kalasapur (KPR) soil series are having deep soil depth cover around 8.12% of area, respectively and Nagavi Tanda (NGT) soil series are having very deep soil depth covers around 7.42 % of area, all these are soil series major crop is maize.  The total cost of cultivation and benefit cost ratio (BCR) in study area for maize ranges between Rs.37277/ha in KPR soil (with BCR of 3.08) and Rs.9961/ha in HRV soil (with BCR of 2.85).  The land management practices reported by the farmers are crop rotation, tillage practices, fertilizer application and use of farm yard manure (FYM). Due to higher wages farmer are following labour saving strategies is not prating soil and water conservation measures. Less ownership of livestock limiting application of FYM.  It was observed soil quality influences on the type and intensity of land use. More fertilizer applications in deeper soil to maximize returns. Suggestions;  Involving farmers is watershed planning helps in strengthing institutional participation.  The per capita food consumption and monthly income is very low. Diversifying income generation activities from crop and livestock production in order to reduce risk related to drought and market prices.  Majority of farmers reported that they are not getting timely support/extension services from the concerned development departments.  By strengthing agricultural extension for providing timely advice improved technology there is scope to increase in net income of farm households.  By adopting recommended package of practices by following the soil test fertiliser recommendation, there is scope to increase yield in maize (33.4 to79.2%). ; Watershed Development Department, Government of Karnataka (World Bank Funded) Sujala –III Project

Not Available ; The land resource inventory of Bhimnalli microwatershed was conducted using village cadastral maps and IRS satellite imagery on 1:7920 scale. The false colour composites of IRS imagery were interpreted for physiography and these physiographic delineations were used as base for mapping soils. The soils were studied in several transects and a soil map was prepared with phases of soil series as mapping units. Random checks were made all over the area outside the transects to confirm and validate the soil map unit boundaries. The soil map shows the geographic distribution and extent, characteristics, classification and use potentials of the soils in the microwartershed. The present study covers an area of 643 ha in Bhimnalli microwatershed in Gulbarga taluk of Gulbarga district, Karnataka. The climate is semiarid and categorized as drought prone with an average annual rainfall of 740 mm, of which about 540 mm is received during south–west monsoon, 126 mm during north-east and the remaining 74 mm during the rest of the year. An area of about 97 per cent is covered by soils, three per cent by waterbodies, settlements and others. The salient findings from the land resource inventory are summarized briefly below.  The soils belong to 11 soil series and 34 soil phases (management units) and 7 land use classes.  The length of crop growing period is about 120-150 days starting from the 3rd week of May to 1rd week of October.  From the master soil map, several interpretative and thematic maps like land capability, soil depth, surface soil texture, soil gravelliness, available water capacity, soil slope and soil erosion were generated.  Soil fertility status maps for macro and micronutrients were generated based on the surface soil samples collected at every 250 m grid interval.  Land suitability for growing major agricultural and horticultural crops were assessed and maps showing degree of suitability along with constraints were generated.  About 97 per cent area is suitable for agriculture and 3 per cent is not suitable for agriculture but well suited for forestry, pasture, agroforestry, silvi-pasture, recreation, installation of wind mills and as habitat for wildlife.  About 29 per cent of the soils are moderately deep to deep (75-150 cm), 2 per cent of the soils are very deep (>150cm), 54 per cent are shallow to moderately shallow (25- 75 cm) and about 13 per cent are very shallow (200mm/m) in available water capacity, 16 per cent medium (100-150 mm/m) and about 76 per cent low (51- 100 mm/m) and very low (0.75%) and 1 per cent low (337 kg/ha) and 29 per cent low (20 ppm).  Available boron is low (1.0 ppm).  Available iron, manganese and copper are sufficient in all the soils.  About 23 per cent area has soils that are deficient (0.6 ppm).  The land suitability for 19 major crops grown in the microwatershed was assessed and the areas that are highly suitable (S1) and moderately suitable (S2) are given below. It is however to be noted that a given soil may be suitable for various crops but what specific crop to be grown may be decided by the farmer looking to his capacity to invest on various inputs, marketing infrastructure, price and finally the demand and supply position. Land suitability for various crops in the microwatershed Crop Suitability Area in ha (%) Crop Suitability Area in ha (%) Highly suitable (S1) Moderately suitable (S2) Highly suitable (S1) Moderately suitable (S2) Sorghum 80 (12) 71 (11) Guava - 174(21) Maize - 54 (8) Jackfruit - 6(1) Red gram - 137 (21) Jamun - 100(15) Sunflower 80 (12) - Musambi 43 (7) 131(20) Cotton 43 (7) 108 (17) Lime 43 (7) 131(20) Sugarcane - - Cashew 6(1) 13(2) Soybean 80(12) 57 (9) Custard apple 157 (24) 286(44) Bengalgram 137(21) 81(13) Amla 157 (24) 119 (18) Mango - 6(1) Tamarind - 113 (17) Sapota - 161(25) Apart from the individual crop suitability, a proposed crop plan has been prepared for the 7 identified LUCs by considering only the highly and moderately suitable lands for different crops and cropping systems with food, fibre and horticulture crops that helps in maintaining the ecological balance in microwatershed  Maintaining soil-health is vital to crop production and conserve soil and land resource base for maintaining ecological balance and to mitigate climate change. For this, several ameliorative measures have been suggested to these problematic soils like saline/alkali, highly eroded, sandy soils etc.,  Soil and water conservation treatment plan has been prepared that would help in identifying the sites to be treated and also the type of structures required.  As part of the greening programme, several tree species have been suggested to be planted in marginal and submarginal lands, field bunds and also in the hillocks, mounds and ridges. Baseline socioeconomic characterisation is prerequisite to prepare action plan for program implementation and to assess the project performance before making any changes in the watershed development program. The baseline provides appropriate policy direction for enhancing productivity and sustainability in agriculture. Methodology: Bhimnalli Microwatershed (Kamalapur sub-watershed, Gulbarga taluk, Gulbarga district) is located in between 17036' – 17038' North latitudes and 7700' – 7702' East longitudes, covering an area of about 643 ha, bounded by Dhanura, Bachinal, Mormanchi and Kurnur villages with length of growing period (LGP) 120-150 days. We used soil resource map as basis for sampling farm households to test the hypothesis that soil quality influence crop selection, and conservation investment of farm households. The level of technology adoption and productivity gaps and livelihood patterns were analyses. The cost of soil degradation and ecosystem services were quantified. Results: The socio-economic outputs for Bhimnalli Microwatershed Gulbarga taluk and district are presented here. Social Indicators;  Male and female ratio is 59.1 to 40.9 per cent to the total sample population.  Younger age 18 to 50 years group of population is around 47.8 per cent to the total population.  Literacy population is around 68.2 per cent.  Social groups belong to scheduled caste (SC) is around 50 per cent.  Fire wood is the source of energy for a cooking among 50 per cent.  About 10 per cent of households have a yashaswini health card.  Dependence on ration cards for food grains through public distribution system among all sample households.  Swach bharath program providing closed toilet facilities around 50 per cent of sample households.  Women participation in decisions making are around 90 per cent of households were found. Economic Indicators;  The average land holding is 2.6 ha indicates that majority of farm households are belong to small and medium and large farmers. The dry land is total cultivated land area among all the sample farmers. 2  Agriculture is the main occupation among 45.5 per cent and agriculture is the main and agriculture labour is subsidiary occupation for 40.9 per cent of sample households.  The average value of domestic assets is around Rs. 13980 per household. Mobile and television are popular media mass communication.  The average value of farm assets is around Rs. 161200 per household, about 40 per cent, of sample farmer having plough.  The average value of livestock is around Rs. 37292 per household; around 80 per cent of sample household are having livestock.  The average per capita food consumption is around 953.4 grams (2288.91 kilo calories) against national institute of nutrition (NIN) recommendation at 827 gram. Around 70 per cent of sample households are consuming less than the NIN recommendation.  The annual average income is around Rs. 55782 per household. About 60 per cent of farm households are below poverty line.  The per capita monthly average expenditure is around Rs.2266. Environmental Indicators-Ecosystem Services;  The value of ecosystem service helps to support investment to decision on soil and water conservation and in promoting sustainable land use.  The onsite cost of different soil nutrients lost due to soil erosion is around Rs. 3008 per ha/year. The total cost of annual soil nutrients is around Rs. 1883220 per year for the total area of 642.74 ha.  The average value of ecosystem service for food grain production is around Rs 10350/ha/year. Per hectare food grain production services is maximum in red gram (Rs.17261) followed by sorghum (Rs. 3440).  The average value of ecosystem service for fodder production is around Rs. 988/ ha/year in sorghum.  The data on water requirement for producing one quintal of grain is considered for estimating the total value of water required for crop production. The per hectare value of water used and value of water was maximum in redgram (Rs. 62920) followed by sorghum (Rs. 47054). Economic Land Evaluation;  The major cropping pattern is redgram (36.9 %) followed by greengram (27.11 %) and sorghum (9.0 %).  In Bhimnalli Microwatershed, major soil is Novinihala (NHA) series having shallow soil depth cover around 5.82 % of area. On this soil farmers are presently growing redgram, sorghum, Mahagaon (MAN) series having very deep soil depth cover around 1.77 % of area, the crops are red gram, 3 Kalamundargi (KGI) soil series are having shallow soil depth cover around 0.9 % of areas; crops are redgram, Ramnelli (RMN) soil series having deep soil depth cover around 3.75 % of area; crops are redgram, Rajnala (RML) soil series deep soil depth cover around 4.55 % of area. The major crops grown redgram, Dinsi (DSI) soil series moderately shallow soil depth cover around 2.41 % of area, the major crop grown is red gram.  The total cost of cultivation and benefit cost ratio (BCR) in study area for red gram ranges between Rs. 39379/ha in RNL soil (with BCR of 1.44) and Rs. 24845 /ha in MAN soil (with BCR of 1.72).  In sorghum the cost of cultivation in NHA soil Rs 24348/ha (with BCR of 1.18).  The land management practices reported by the farmers are crop rotation, tillage practices, fertilizer application and use of farm yard manure (FYM). Due to higher wages farmer are following labour saving strategies is not prating soil and water conservation measures. Less ownership of livestock limiting application of FYM.  It was observed soil quality influences on the type and intensity of land use. More fertilizer applications in deeper soil to maximize returns. Suggestions;  Involving farmers is watershed planning helps in strengthing institutional participation.  The per capita food consumption and monthly income is very low. Diversifying income generation activities from crop and livestock production in order to reduce risk related to drought and market prices.  Majority of farmers reported that they are not getting timely support/extension services from the concerned development departments.  By strengthing agricultural extension for providing timely advice improved technology there is scope to increase in net income of farm households.  By adopting recommended package of practices by following the soil test fertiliser recommendation, there is scope to increase yield in red gram (0 to 45 %) and sorghum (9.9 %). ; Watershed Development Department, Government of Karnataka (World Bank Funded) Sujala –III Project

Not Available ; The land resource inventory of Dharjamga-1 microwatershed was conducted using village cadastral maps and IRS satellite imagery on 1:7920 scale. The false colour composites of IRS imagery were interpreted for physiography and these physiographic delineations were used as base for mapping soils. The soils were studied in several transects and a soil map was prepared with phases of soil series as mapping units. Random checks were made all over the area outside the transects to confirm and validate the soil map unit boundaries. The soil map shows the geographic distribution and extent, characteristics, classification and use potentials of the soils in the microwartershed. The present study covers an area of 830 ha in Dharjamga-1 microwatershed in Gulbarga taluk of Gulbarga district, Karnataka. The climate is semiarid and categorized as drought-prone with an average annual rainfall of 740 mm, of which about 540 mm is received during south–west monsoon, 126 mm during north-east and the remaining 74 mm during the rest of the year. An area of about 97 per cent is covered by soils, three per cent by waterbodies, settlements and others. The salient findings from the land resource inventory are summarized briefly below.  The soils belong to 9 soil series and 22 soil phases (management units) and 5 land use classes.  The length of crop growing period is about 120-150 days starting from the 3rd week of May to 1rd week of October.  From the master soil map, several interpretative and thematic maps like land capability, soil depth, surface soil texture, soil gravelliness, available water capacity, soil slope and soil erosion were generated.  Soil fertility status maps for macro and micronutrients were generated based on the surface soil samples collected at every 250 m grid interval.  Land suitability for growing major agricultural and horticultural crops was assessed and maps showing degree of suitability along with constraints were generated.  About 87 per cent area is suitable for agriculture and 13 per cent is not suitable for agriculture but well suited for forestry, pasture, agro-forestry, silvi-pasture, recreation, installation of wind mills and as habitat for wildlife.  About 13 per cent of the soils are moderately deep to deep (75-150 cm), 66 per cent are shallow to moderately shallow (25-75 cm) and about 20 per cent are very shallow (200mm/m) in available water capacity, 41 per cent medium (100-150 mm/m) and about 53 per cent low (51-100 mm/m) and very low (0.75%) in organic carbon.  An area of 8 per cent has soils that are low (337 kg/ha) and about 1 per cent low (20 ppm).  Available boron is low (4.5 ppm).  Available manganese and copper are sufficient in all the soils.  About 56 per cent deficient (0.6 ppm).  The land suitability for 19 major crops grown in the microwatershed was assessed and the areas that are highly suitable (S1) and moderately suitable (S2) are given below. It is however to be noted that a given soil may be suitable for various crops but what specific crop to be grown may be decided by the farmer looking to his capacity to invest on various inputs, marketing infrastructure, price and finally the demand and supply position. Land suitability for various crops in the microwatershed Crop Suitability Area in ha (%) Crop Suitability Area in ha (%) Highly suitable (S1) Moderately suitable (S2) Highly suitable (S1) Moderately suitable (S2) Sorghum 94 (11) 267 (32) Guava - - Maize - - Jackfruit - - Red gram - 361 (43) Jamun - 23(3) Sunflower 23 (3) 71 (9) Musambi 23 (3) 71(9) Cotton 23 (3) 338 (41) Lime 23 (3) 71(9) Sugarcane - - Cashew - - Soybean 76(9) 285 (34) Custard apple 94 (11) 267(32) Bengalgram 361(43) 282 (34) Amla 94 (11) 267(32) Mango - - Tamarind - 23 (3) Sapota - - Apart from the individual crop suitability, a proposed crop plan has been prepared for the 5 identified LUCs by considering only the highly and moderately suitable lands for different crops and cropping systems with food, fibre and horticulture crops that helps sustained production and also in maintaining the ecological balance in microwatershed  Maintaining soil-health is vital to crop production and conserve soil and land resource base for maintaining ecological balance and to mitigate climate change. For this, several ameliorative measures have been suggested to these problematic soils like saline/alkali, highly eroded, sandy soils etc.,  Soil and water conservation treatment plan has been prepared that would help in identifying the sites to be treated and also the type of structures required.  As part of the greening programme, several tree species have been suggested to be planted in marginal and submarginal lands, field bunds and also in the hillocks, mounds and ridges. Baseline socioeconomic characterisation is prerequisite to prepare action plan for program implementation and to assess the project performance before making any changes in the watershed development program. The baseline provides appropriate policy direction for enhancing productivity and sustainability in agriculture. Methodology: Dharjamga-1 Microwatershed (Sonath sub-watershed, Gulbarga taluk, Gulbarga district) is located in between 17037' – 17039' North latitudes and 7703' – 7705' East longitudes, covering an area of about 830 ha, bounded by Kinhi, Dongaragaon, Bhimnalli, Sonath, Wahadi and Gobbarwadi villages with length of growing period (LGP) 120-150 days. We used soil resource map as basis for sampling farm households to test the hypothesis that soil quality influence crop selection, and conservation investment of farm households. The level of technology adoption and productivity gaps and livelihood patterns were analyses. The cost of soil degradation and ecosystem services were quantified. Results: The socio-economic outputs for Dharjamga-1 micro-watershed (Sonath subwatershed, Gulbarga taluk, Gulbarga district) are presented here. Social Indicators;  Male and female ratio is 63.2 to 36.8 per cent to the total sample population.  Younger age 18 to 50 years group of population is around 57.9 per cent to the total population.  Literacy population is around 42.1 per cent.  Social groups belong to other backward caste (OBC) is around 50.0 per cent.  Fire wood is the source of energy for a cooking among 90 per cent.  About 80.0 per cent of households have a yashaswini health card.  Dependence on ration cards for food grains through public distribution system is around 50 per cent.  Swachha bharath program providing closed toilet facilities around 10 per cent of sample households.  Women participation in decisions making of agriculture productivity of among the all sample households was found. Economic Indicators;  The average land holding is 0.83 ha indicates that majority of farm households are belong to marginal and small farmers. The total cultivated area by dry land condition among the sample households. 2  Agriculture is the main occupation among 53.1 per cent and agriculture is the main and agriculture labour is subsidiary occupation for 40.6 per cent of sample households.  The average value of domestic assets is around Rs. 24500 per household. Mobile and television are popular media mass communication.  The average livestock value is around Rs. 43600 per household; about 50 per cent of household are having livestock.  The average per capita food consumption is around 776.4 grams (1727 kilo calories) against national institute of nutrition (NIN) recommendation at 827 gram. Around 100 per cent of sample households are consuming less than the NIN recommendation.  The annual average income is around Rs. 41320 per household. About 80 per cent of farm households are below poverty line.  The per capita average monthly expenditure is around Rs. 2294. Environmental Indicators-Ecosystem Services;  The value of ecosystem service helps to support investment to decision on soil and water conservation and in promoting sustainable land use.  The onsite cost of different soil nutrients lost due to soil erosion is around Rs. 2718 per ha/year. The total cost of annual soil nutrients is around Rs. 2190754 per year for the total area of 830.21 ha.  The average value of ecosystem service for food grain production is around Rs 22897/ha/year of red gram.  The data on water requirement for producing one quintal of grain is considered for estimating the total value of water required for crop production. The per hectare value of water used and value of water was in red gram (Rs.61122). Economic Land Evaluation;  The major cropping pattern is red gram (100 %).  In Dharjamga-1 Micro-watershed, major soil of Basaltic landforms of Margutti series is having very shallow soil depth cover around 5.7 % of area. On this soil farmers are presently growing red gram, soil of Matki series is having very shallow soil depth cover around 2.8 % of area. On this soil farmers are presently growing red gram, soil of Novinihal series is having shallow soil depth cover around 30.1% of area. On this soil farmers are presently growing red gram, soil of Bhimanahalli series is having shallow soil depth cover around 3.8 % of area. On this soil farmers are presently growing red gram, soil of gutti series is having moderately shallow soil depth cover around 4.4% of area. On this soil farmers are presently growing red gram, soil of Kamalapur series is 3 having moderately deep soil depth cover around 8.5 % of area. On this soil farmers are presently growing red gram.  The total cost of cultivation and benefit cost ratio (BCR) in study area for red gram ranges between Rs.29890/ha in NHA soil (with BCR of 1.57) and Rs.14968/ha in MGT soil (with BCR of 2.74).  The land management practices reported by the farmers are crop rotation, tillage practices, fertilizer application and use of farm yard manure (FYM). Due to higher wages farmer are following labour saving strategies is not prating soil and water conservation measures. Less ownership of livestock limiting application of FYM.  It was observed soil quality influences on the type and intensity of land use. More fertilizer applications in deeper soil to maximize returns. Suggestions;  Involving farmers is watershed planning helps in strengthing institutional participation.  The per capita food consumption and monthly income is very low. Diversifying income generation activities from crop and livestock production in order to reduce risk related to drought and market prices.  Majority of farmers reported that they are not getting timely support/extension services from the concerned development departments.  By strengthing agricultural extension for providing timely advice improved technology there is scope to increase in net income of farm households.  By adopting recommended package of practices by following the soil test fertiliser recommendation, there is scope to increase yield in red gram (3.6 to 22.4%). ; Watershed Development Department, Government of Karnataka (World Bank Funded) Sujala –III Project

Not Available ; The land resource inventory of Padasavli-1 microwatershed was conducted using village cadastral maps and IRS satellite imagery on 1:7920 scale. The false colour composites of IRS imagery were interpreted for physiography and these physiographic delineations were used as base for mapping soils. The soils were studied in several transects and a soil map was prepared with phases of soil series as mapping units. Random checks were made all over the area outside the transects to confirm and validate the soil map unit boundaries. The soil map shows the geographic distribution and extent, characteristics, classification and use potentials of the soils in the microwartershed. The present study covers an area of 535 ha in Padasavli-1 microwatershed in Aland taluk of Kalaburgi district, Karnataka. The climate is semiarid and categorized as drought prone with an average annual rainfall of 786 mm of which about 595 mm is received during south –west monsoon, 116 mm during north-east and the remaining 75 mm during the rest of the year. An area of about 95 per cent is covered by soils, five per cent by waterbodies, settlements and others. The salient findings from the land resource inventory are summarized briefly below.  The soils belong to 7 soil series and 16 soil phases (management units) and 5 land management units.  The length of crop growing period is about 150 days starting from the 3rd week of June to 1rd week of October.  From the master soil map, several interpretative and thematic maps like land capability, soil depth, surface soil texture, soil gravelliness, available water capacity, soil slope and soil erosion were generated.  Soil fertility status maps for macro and micronutrients were generated based on the surface soil samples collected at every 250 m grid interval.  Land suitability for growing major agricultural and horticultural crops were assessed and maps showing degree of suitability along with constraints were generated.  About 95 per cent area is suitable for agriculture  About 11 per cent of the soils are very deep (>150 cm) to moderately deep (75-100 cm), 73 per cent are moderately shallow to shallow (25-75 cm) and about 11 per cent are very shallow (200mm/m) in available water capacity, 18 per cent medium (100-150 mm/m) and about 68 per cent low (50-100 mm/m) and very low (0.75%) and 14 per cent low (57 kg/ha) in available phosphorus.  About 23 per cent medium (145-337 kg/ha) and 72 per cent high (>337 kg/ha) in available potassium.  Available sulphur is low (20 ppm).  Available boron is low (1 ppm) in available boron.  About 8 per cent area has soils that are deficient (0.6 ppm).  Available manganese and copper are sufficient in all the soils.  About 69 per cent area has soils that are deficient (0.6 ppm).  The land suitability for 18 major crops (agricultural and horticultural) grown in the microwatershed were assessed and the areas that are highly suitable (S1) and moderately suitable (S2) are given below. It is however to be noted that a given soil may be suitable for various crops but what specific crop to be grown may be decided by the farmer looking to his capacity to invest on various inputs, marketing infrastructure, price, and finally the demand and supply position. Land suitability for various crops in the microwatershed Crop Suitability Area in ha (%) Crop Suitability Area in ha (%) Highly suitable (S1) Moderately suitable (S2) Highly suitable (S1) Moderately suitable (S2) Sorghum 33 (6) 131(25) Sapota - - Maize - - Jackfruit - - Red gram - 164 (31) Jamun - 49 (9) Sunflower 33(6) 24 (5) Musambi 33(6) 24 (5) Cotton 33 (6) 131 (25) Lime 33(6) 24 (5) Sugarcane - - Cashew - - Soybean 33(6) 131 (25) Custard apple 33(6) 131(25) Guava - - Amla 33(6) 131(25) Mango - - Tamarind - 49 (9) Apart from the individual crop suitability, a proposed crop plan has been prepared for the 5 identified LMUs by considering only the highly and moderately suitable lands for different crops and cropping systems with food, fibre and horticulture crops that helps in maintaining the ecological balance in the microwatershed.   Maintaining soil-health is vital to crop production and conserve soil and land resource base for maintaining ecological balance and to mitigate climate change. For this, several ameliorative measures have been suggested to these problematic soils like saline/alkali, highly eroded, sandy soils etc.,  Soil and water conservation treatment plan has been prepared that would help in identifying the sites to be treated and also the type of structures required.  As part of the greening programme, several tree species have been suggested to be planted in marginal and submarginal lands and also in the field bunds, hillocks, mounds and ridges. Baseline socioeconomic characterisation is prerequisite to prepare action plan for program implementation and to assess the project performance before making any changes in the watershed development program. The baseline provides appropriate policy direction for enhancing productivity and sustainability in agriculture. Methodology: Padasavli-1 micro-watershed (Padasavli sub-watershed, Aland taluk, Gulbarga district) is located in between 17035'–17036' North latitudes and 76025'– 76028' East longitudes, covering an area of about 534.63 ha, bounded by Chincholi Khurd, Hiroli, Nagalogaon and Matki villages with length of growing period (LGP) 120- 150 days. We used soil resource map as basis for sampling farm households to test the hypothesis that soil quality influence crop selection, and conservation investment of farm households. The level of technology adoption and productivity gaps and livelihood patterns were analyses. The cost of soil degradation and ecosystem services were quantified. Results: The socio-economic outputs for Padasavli-1 micro-watershed (Padasavli subwatershed, Aland taluk, Gulbarga district) are presented here. Social Indicators  Male and female ratio is 57 to 42.1 Per cent to the total sample population.  Younger age 18 to 50 years group of population is 60.2 around per cent to the total population.  Literacy population is around 76.4 per cent.  Social groups belong to other backward caste (OBC) among all sample households.  Firewood is the source of energy for a cooking among all sample households.  About 20 per cent of households have a yashaswini health card.  Dependence on ration cards for food grains through public distribution system is around 89 per cent of sample households.  Swach bharath program providing closed toilet facilities around 30 per cent of sample households  Women participation in decisions making for agriculture production among all the sample households. Economic Indicators  The average land holding is 2.67 ha indicates that majority of farm households are belong to small and medium farmers. The total cultivated area by dry land condition among the sample farmers.  Agriculture is the main occupation among 44.7 per cent and agriculture is the main and agriculture labour is a subsidiary occupation about 55.3 per cent of sample households. 2  The average value of domestic assets is around Rs. 6833. per household. Mobile and television are popular media mass communication.  The average value of farm assets is around Rs. 3721 per household, about 50 per cent of sample farmers having plough and bullock cart (50 %).  The average value of livestock is around Rs. 28125 per household; about 78.5 per cent of household are having livestock.  The average per capita food consumption is around 844 grams (1774 kilo calories) against national institute of nutrition (NIN) recommendation at 827 gram. Around 60 per cent of sample households are consuming less than the NIN recommendation.  The annual average income is around Rs. 65120 per household. About 70 per cent of farm households are below poverty line.  The per capita average monthly expenditure is around Rs.1995. Environmental Indicators-Ecosystem Services  The value of ecosystem service helps to support investment to decision on soil and water conservation and in promoting sustainable land use.  The onsite cost of different soil nutrients lost due to soil erosion is around Rs. 1260 per ha/year. The total cost of annual soil nutrients is around Rs. 640239 per year for the total area of 534 ha.  The average value of ecosystem service for food grain production is around Rs 7231/ ha/year. Per hectare food grain production services is maximum in red gram (Rs. 15388) followed by sunflower (Rs. 5371) and greengram (Rs.934).  The data on water requirement for producing one quintal of grain is considered for estimating the total value of water required for crop production. The per hectare value of water used and value of water was maximum in red gram (Rs. 42840), followed by green gram (Rs. 34116) and sunflower (Rs. 24122). Economic Land Evaluation  The major cropping pattern is red gram (83.7 %) followed by green gram (8.7 %) and sunflower (7.6 %).  In Padasavali-1 Microwatershed, major soil series are Novinihala series are having shallow soil depth covers around 38.7 % of area the major crops are green gram (60 %) and redgram (40 %). Mahagaon soil series having are very deep soils depth covers around 9.22 % of area the crops are redgram. Marugutti soil series are having very shallow depth covers around 9.2 % of area the crops are redgram (44.4 %) and sunflower (55.6 %). Gutti soil series are having moderately shallow depth covers around (4.64) of area the crops are red gram.  The total cost of cultivation and benefit cost ratio (BCR) in study area for red gram ranges between Rs. 32931/ha in NHA soil (with BCR of 1.13) and Rs. 18116/ha in MAN soil (with BCR of 2.21). 3  In sunflower the cost of cultivation in MGT soil is Rs.16128/ha (with BCR of 1.33) and green gram the cost of cultivation in NHA soil is Rs.18826/ha (with BCR of 1.08).  The land management practices reported by the farmers are crop rotation, tillage practices, fertilizer application and use of farm yard manure (FYM). Due to higher wages farmer are following labour saving strategies is not prating soil and water conservation measures. Less ownership of livestock limiting application of FYM.  It was observed soil quality influences on the type and intensity of land use. More fertilizer applications in deeper soil to maximize returns. Suggestions  Involving farmers is watershed planning helps in strengthing institutional participation.  The per capita food consumption and monthly income is very low. Diversifying income generation activities from crop and livestock production in order to reduce risk related to drought and market prices.  Majority of farmers reported that they are not getting timely support/extension services from the concerned development departments.  By strengthing agricultural extension for providing timely advice improved technology there is scope to increase in net income of farm households.  By adopting recommended package of practices by following the soil test fertiliser recommendation, there is scope to increase yield in red gram (40.1 to 50.3 %), followed by sunflower (56.0 %) and greengram (42.2 %). ; Watershed Development Department, Government of Karnataka (World Bank Funded) Sujala –III Project

Not Available ; The land resource inventory of Govankop-1 Microwatershed was conducted using village cadastral maps and IRS satellite imagery on 1:7920 scale. The false colour composites of IRS imagery were interpreted for physiography and the physiographic delineations were used as base for mapping soils. The soils were studied in several transects and a soil map was prepared with phases of soil series as mapping units. Random checks were made all over the area outside the transects to confirm and validate the soil map unit boundaries. The soil map shows the geographic distribution and extent, characteristics, classification and use potentials of the soils in the microwartershed. The present study covers an area of 600 ha in Shirahatti taluk of Gadag district, Karnataka. The climate is semiarid and categorized as drought- prone with an average annual rainfall of 633 mm of which about 363 mm is received during south –west monsoon, 165 mm during north-east and the remaining 105 mm during the rest of the year. An area of about 96 per cent is covered by soils, four per cent by waterbodies, settlements and others. The salient findings from the land resource inventory are summarized briefly below.  The soils belong to 11 soil series and 32 soil phases (management units) and 7 land management units.  The length of crop growing period is about 150 days starting from the 3rd week of June to 1st week of October.  From the master soil map, several interpretative and thematic maps like land capability, soil depth, surface soil texture, soil gravelliness, available water capacity, soil slope and soil erosion were generated.  Soil fertility status maps for macro and micronutrients were generated based on the surface soil samples collected at every 250 m grid interval.  Land suitability for growing major agricultural and horticultural crops were assessed and maps showing the degree of suitability along with constraints were generated.  About 96 per cent area is suitable for agriculture.  About 9 per cent of the soils are deep (100 - 150 cm) to moderately deep (75-100 cm), 59 per cent are moderately shallow to shallow (25-75 cm) and about 28 per cent are very shallow (9.0).  The Electrical Conductivity (EC) of the soils are dominantly 0.75%) in organic carbon.  Entire area in the microwatershed is low (337 kg/ha) in available potassium.  Available sulphur is low (20 ppm).  Available boron is low (0.5 ppm) in about 52 per cent area, medium (0.5-1.0 ppm) in 21 per cent area and high (>1.0 ppm) in 23 per cent area.  Available iron is deficient in about 15 per cent area and sufficient in 81 per cent area.  Available manganese and copper are sufficient in all the soils.  Available zinc is sufficient (>0.6 ppm) in 4 per cent and deficient (<0.6 ppm) in 92 per cent area of the Microwatershed.  The land suitability for 21 major crops grown in the Microwatershed were assessed and the areas that are highly suitable (S1) and moderately suitable (S2) are given below. It is however to be noted that a given soil may be suitable for various crops but what specific crop to be grown may be decided by the farmer looking to his capacity to invest on various inputs, marketing infrastructure, price and finally the demand and supply position. Land suitability for various crops in the Microwatershed Crop Suitability Area in ha (%) Crop Suitability Area in ha (%) Highly suitable (S1) Moderately suitable (S2) Highly suitable (S1) Moderately suitable (S2) Sorghum - 191 (32) Jackfruit - 16 (3) Maize - 72 (12) Jamun - - Bengalgram - 146 (24) Musambi - 52 (9) Groundnut - 72 (12) Lime - 16 (3) Sunflower - 52 (9) Cashew - 16 (3) Cotton - 138 (23) Custard Apple - 108 (18) Banana - 52 (9) Amla - 108 (18) Pomegranate - 52 (9) Tamarind - 16 (3) Mango - 16 (3) Marigold - 138 (23) Sapota - 16(3) Chrysanthemum - 138 (23) Guava - 16 (3) Apart from the individual crop suitability, a proposed crop plan has been prepared for the 7 identified LMUs by considering only the highly and moderately suitable lands for different crops and cropping systems with food, fibre and horticulture crops.  Maintaining soil-health is vital to crop production and conserve soil and land resource base for maintaining ecological balance and to mitigate climate change. For this, several ameliorative measures have been suggested to these problematic soils like saline/alkali, highly eroded, sandy soils etc.,  Soil and water conservation treatment plan has been prepared that would help in identifying the sites to be treated and also the type of structures required.  As part of the greening programme, several tree species have been suggested to be planted in marginal and submarginal lands and also in the hillocks, mounds and ridges. SOCIO-ECONOMIC STATUS OF FARM HOUSEHOLDS Baseline socioeconomic characterisation is prerequisite to prepare action plan for program implementation and to assess the project performance before making any changes in the watershed development program. The baseline provides appropriate policy direction for enhancing productivity and sustainability in agriculture. Methodology: Govankop-1 micro-watershed (Kanakvad sub-watershed, Shirahatti taluk, Gadag district) is located in between 1500' – 1501' North latitudes and 75038' – 75041' East longitudes, covering an area of about 600 ha, bounded by Kerikoppa, Belhatti, Kanakvad and Kerikoppa villages with length of growing period (LGP) 150-180 days. We used soil resource map as basis for sampling farm households to test the hypothesis that soil quality influence crop selection, and conservation investment of farm households. The level of technology adoption and productivity gaps and livelihood patterns were analyses. The cost of soil degradation and ecosystem services were quantified. Results: The socio-economic outputs for the Govankop-1 micro-watershed (Kanakvad sub-watershed, Shirahatti taluk, Gadag district) are presented here. Social Indicators;  Male and female ratio is 52.3 to 47.7 per cent to the total sample population.  Younger age 18 to 50 years group of population is around 67.8 per cent to the total population.  Literacy population is around 80 per cent.  Social groups belong to other backward caste (SC) is around 80 per cent.  Fire wood is the source of energy for a cooking among 80 per cent.  About 70 per cent of households have a yashaswini health card.  Majority of farm households (50 %) are having MGNREGA card for rural employment.  Dependence on ration cards for food grains through public distribution system is around 70 per cent of sample households.  Swach bharath program providing closed toilet facilities around 80 per cent of sample households.  Institutional participation is only 1.5 per cent of sample households.  Women participation in decisions making is among all the households were found. Economic Indicators;  The average land holding is 1.02 ha indicates that majority of farm households are belong to small and medium farmers. The dry land of 80.6 % and irrigated land 19.4 % of total cultivated land area among the sample farmers. 2  Agriculture is the main occupation and agriculture labour is subsidiary occupation among 90.8 per cent and agriculture is the main and government services are a subsidiary occupation for 1.5 per cent of sample households.  The average value of domestic assets is around Rs. 97362 per household. Mobile and television are popular media mass communication.  The average farm assets value is around Rs. 142619 per household, about 30 per cent of sample farmers having plough and sprayer.  The average livestock value is around Rs. 29731 per household; about 71.43 per cent of household are having livestock.  The average per capita food consumption is around 1014 grams (2227.5 kilo calories) against national institute of nutrition (NIN) recommendation at 827 gram. Among all sample households are consuming less than the NIN recommendation.  The annual average income is around Rs.16631 per household. About 100 per cent of farm households are below poverty line.  The per capita monthly average expenditure is around Rs.1929. Environmental Indicators-Ecosystem Services;  The value of ecosystem service helps to support investment to decision on soil and water conservation and in promoting sustainable land use.  The onsite cost of different soil nutrients lost due to soil erosion is around Rs. 1044 per ha/year. The total cost of annual soil nutrients is around Rs. 600606 per year for the total area of 600.4 ha.  The average value of ecosystem service for food grain production is around Rs. 3187/ha/year in maize crops.  The average value of ecosystem service for fodder production is around Rs. 2805/ ha/year.  The data on water requirement for producing one quintal of grain is considered for estimating the total value of water required for crop production. The per hectare value of water used and value of water was maximum in maize (Rs. 27159). Economic Land Evaluation;  The major cropping pattern is maize (100 %).  In Govinkoppa-1 micro-watershed, major soil is Hanganakatti (HGK) and Shirol (SRL) soil series is having very shallow soil depth cover around 10.40 per cent and 17.43 per cent of areas, respectively. On this soil farmers are presently growing maize. Yelisirunj (YSJ) and Beladadi (BLD) soil series are having shallow soil depth cover around 6.38 per cent and 8.85 per cent of area, respectively the crop is maize. Kabulayathakatti Tanda (KKT), Attikatti Tanda (ATT) and Venkatapur (VKP) soil series are having moderately shallow soil 3 depth covers around 12.24 per cent, 5.0 per cent and 13.89 per cent of areas, respectively on crop is maize. Jelligeri (JLG) soil is having moderately deep soil depth cover around 6.0 per cent of area the crop on maize.  The total cost of cultivation and benefit cost ratio (BCR) in study area for maize ranges between Rs.48232/ha in BLD soil (with BCR of 1.34) and Rs.12643/ha in YSJ soil (with BCR of 1.80).  The land management practices reported by the farmers are crop rotation, tillage practices, fertilizer application and use of farm yard manure (FYM). Due to higher wages farmer are following labour saving strategies is not prating soil and water conservation measures. Less ownership of livestock limiting application of FYM.  It was observed soil quality influences on the type and intensity of land use. More fertilizer applications in deeper soil to maximize returns. Suggestions;  Involving farmers is watershed planning helps in strengthing institutional participation.  The per capita food consumption and monthly income is very low. Diversifying income generation activities from crop and livestock production in order to reduce risk related to drought and market prices.  Majority of farmers reported that they are not getting timely support/extension services from the concerned development departments.  By strengthing agricultural extension for providing timely advice improved technology there is scope to increase in net income of farm households. By adopting recommended package of practices by following the soil test fertiliser recommendation, there is scope to increase yield in maize (63.1 to 79.8 %). ; Watershed Development Department, Government of Karnataka (World Bank Funded) Sujala –III Project

International audience ; This study focuses on the links between food production and greenhouse gas emissions in the European Union. The analysis relies on two sets of simulations of AROPAj, a supply-side model of EU agriculture: (i) a carbon price affecting agricultural GHG emissions (from 0 to 200 EUR/tCO2eq), and (ii) a lower limit on the net quantity of food calories provided by EU agriculture (200 to 450 Mt soft wheat equivalent). The model is calibrated on six annual datasets 2007–2012. The results show that a moderate increase in the price of carbon would lead to an increase in total areas and outputs of crops. Animal production decreases over the explored range of carbon price. At 200 EUR/tCO2eq, the reduction in GHG emissions ranges from 25 to 35% depending on the year of calibration. The results also show that current net calorie production from food can be more than doubled, while simultaneously reducing GHG emissions by 10–15%. The compatibility between a reduction in GHG emissions and an increase in food calorie production relies on substantial changes in animal production and feed, which implies significant variations in grassland and fallow land. These effects are contrasted between the regions of the EU. ; Cette étude se concentre sur les liens entre la production alimentaire et les émissions de gaz à effet de serre dans l'Union européenne. L'analyse s'appuie sur deux séries de simulations d'AROPAj, un modèle de l'agriculture européenne axé sur l'offre : (i) un prix du carbone affectant les émissions de GES agricoles (de 0 à 200 EUR/tCO2eq), et (ii) une limite inférieure de la quantité nette de calories alimentaires fournies par l'agriculture de l'UE (200 à 450 Mt d'équivalent blé tendre). Le modèle est calibré sur six séries de données annuelles 2007-2012. Les résultats montrent qu'une augmentation modérée du prix du carbone entraînerait une augmentation des superficies totales et de la production des cultures. La production animale diminue dans la fourchette explorée du prix du carbone. À 200 EUR/tCO2eq, la réduction des émissions de GES varie de 25 à 35 % selon l'année de calibrage. Les résultats montrent également que la production actuelle de calories nettes provenant de l'alimentation peut être plus que doublée, tout en réduisant simultanément les émissions de GES de 10 à 15 %. La compatibilité entre une réduction des émissions de GES et une augmentation de la production de calories alimentaires repose sur des changements substantiels dans la production et l'alimentation animale, ce qui implique des variations importantes dans les prairies et les jachères. Ces effets sont contrastés entre les régions de l'UE.

International audience ; This study focuses on the links between food production and greenhouse gas emissions in the European Union. The analysis relies on two sets of simulations of AROPAj, a supply-side model of EU agriculture: (i) a carbon price affecting agricultural GHG emissions (from 0 to 200 EUR/tCO2eq), and (ii) a lower limit on the net quantity of food calories provided by EU agriculture (200 to 450 Mt soft wheat equivalent). The model is calibrated on six annual datasets 2007–2012. The results show that a moderate increase in the price of carbon would lead to an increase in total areas and outputs of crops. Animal production decreases over the explored range of carbon price. At 200 EUR/tCO2eq, the reduction in GHG emissions ranges from 25 to 35% depending on the year of calibration. The results also show that current net calorie production from food can be more than doubled, while simultaneously reducing GHG emissions by 10–15%. The compatibility between a reduction in GHG emissions and an increase in food calorie production relies on substantial changes in animal production and feed, which implies significant variations in grassland and fallow land. These effects are contrasted between the regions of the EU. ; Cette étude se concentre sur les liens entre la production alimentaire et les émissions de gaz à effet de serre dans l'Union européenne. L'analyse s'appuie sur deux séries de simulations d'AROPAj, un modèle de l'agriculture européenne axé sur l'offre : (i) un prix du carbone affectant les émissions de GES agricoles (de 0 à 200 EUR/tCO2eq), et (ii) une limite inférieure de la quantité nette de calories alimentaires fournies par l'agriculture de l'UE (200 à 450 Mt d'équivalent blé tendre). Le modèle est calibré sur six séries de données annuelles 2007-2012. Les résultats montrent qu'une augmentation modérée du prix du carbone entraînerait une augmentation des superficies totales et de la production des cultures. La production animale diminue dans la fourchette explorée du prix du carbone. À 200 EUR/tCO2eq, la réduction des émissions de GES varie de 25 à 35 % selon l'année de calibrage. Les résultats montrent également que la production actuelle de calories nettes provenant de l'alimentation peut être plus que doublée, tout en réduisant simultanément les émissions de GES de 10 à 15 %. La compatibilité entre une réduction des émissions de GES et une augmentation de la production de calories alimentaires repose sur des changements substantiels dans la production et l'alimentation animale, ce qui implique des variations importantes dans les prairies et les jachères. Ces effets sont contrastés entre les régions de l'UE.

Russia and other countries in the commonwealth of independent states that have implemented voucher privatization programs have to account for the puzzling behavior of insiders manager-owners-who, in stripping assets from the firms they own, appear to be stealing from one pocket to fill the other. This article suggests that asset stripping and the absence of restructuring result from interactions between insiders and subnational governments in a particular property rights regime, in which the ability to realize value is limited by uncertainty and illiquidity. As the central institutions that govern the Russian economy have ceded their powers to the provinces, regional and local governments have imposed a variety of distortions on enterprises to protect local employment. To disentangle these vicious circles of control, this article considers three sets of institutional changes: adjustments to the system of fiscal federalism by which subnational governments would be allowed to retain tax revenues generated locally; legal improvements in the protection of property rights; and the provision of mechanisms for restructuring and ownership transformation in insider-dominated firms. The aim of these reforms would be to change the incentives that local governments, owners, and investors face; to convince subnational governments that a more sustainable way of protecting employment lies in protecting local investment; to raise the cost of theft and corruption by insiders and local officials; and to allow investors to acquire controlling stakes in viable firms.

The main object of the analysis presented in the text was to point to and confirm the existence of special "energy cultures" in the European Union. In order to achieve this aim the use was made of research present in the literature, inter alia, in the publications containing statistical analyses by: (1) A. Pach-Gurgul, (2) P. Tapio and his research team – Banister, J. Luukkanen, J. Vehma i R. Willamo, also in a review, (3) Z. Łucki and W. Misiak. Compared with the invoked research, the timeframe of the analysis in the text covered 2011, and the subjective scope embraced 28 countries (EU-28). As part of the research process the following research hypotheses were subjected to verification: (1) It must be assumed that the dissimilarities in energy structures of particular EU member states are an outstanding premise on which to base a recognition of the existence of specific "energy cultures" in the European Union, (2) It must be assumed that in the period of 2001-2011 there occurred changes in the area of "energy cultures" of the European Union, which had earlier been recognised in the literature. In this scope the following conclusions ought to be presented: I. CONCLUSIONS: The differences in energy structures result in the possibility of pointing to particular features characterising member states and clusters of countries, partially because of the predominance of specific energy carriers and/or a way of their conversion. On account of the use of selected indexes for the purpose of characterising the specificity of the European Union member states, six clusters have been distinguished, and they include the following countries: (1) Spain, France, Italy and Great Britain; (2) Bulgaria, the Czech Republic, Estonia and Poland; (3) Denmark, Ireland, Greece, Cyprus, Malta, Austria, Slovenia, Finland and Sweden; (4) Croatia, Latvia, Lithuania, Hungary, Portugal, Romania and Slovakia; (5) Germany; (6) Belgium, Luxembourg and the Netherlands. An observable cluster that recurs in the research by A. Pach-Gurgul as well as in the analysis presented in the text covering 2011, embraces Bulgaria, the Czech Republic, Estonia and Poland (Cluster II). As for Ward's method the cluster is broader, but features an outstanding group of the above-mentioned countries (also including: Croatia, Latvia, Lithuania, Hungary, Slovakia and Romania). Besides, in this model, in comparison with A. Pach-Gurgul's research, another cluster is by and large repeated, including Croatia, Latvia, Lithuania, Hungary, Portugal, Romania and Slovakia – Cluster IV (for a variety of reasons Croatia and Portugal are not repeated). The characteristic feature of both clusters is a higher scale of the index of energy intensity (kgoe/€1000). This shows that it is legitimate to recognise the existence of the division of the European Union into the two "energy cultures": the Western European one and Eastern European one. The main factor behind this division is the energy intensity of the economies of individual member states. Unlike the analysis by P. Tapio and his research team, the axis of division has changed considerably, for within the so-called "old" European Union (EU-15) there was an observable general division into the Northern European and Southern European "energy cultures." Both the above-mentioned clusters (II and IV) can be associated with the "Eastern European culture" as part of the division presented by Z. Łucki and W. Misiak. The energy culture distinguished by the two researchers is to be characterised by: (1) a variety of energy policies, (2) a high energy intensity of the economy, (3) a low electric energy consumption, (4) limited awareness, (5) a negative attitude towards energy market liberalisation. In the case of Bulgaria, the Czech Republic and Poland (Cluster II), the characteristic feature is a considerable share of solid fuels in the energy mix of the gross inland energy consumption. The countries included in Cluster IV are characterised by a smaller share of solid fuels and a higher diversity of energy structure. As part of the k-means clustering method, it is worth pointing out two clusters of countries: Cluster I (Spain, France, Italy, Great Britain) and Cluster V (Germany). The countries in both clusters belong to the so-called "old" European Union, and their main feature is a substantial level of energy production, Germany being the largest producer. In both cases, the characteristic features are a marked share of renewable energy sources, gas as well as petroleum and petroleum products in the gross inland energy consumption. Furthermore, both clusters are characterised by a low or relatively low index of energy intensity (kgoe/€1000). As part of the clustering based on the k-means method, in both periods, that is in 2001 and 2011 the cluster comprising Belgium, Luxembourg and the Netherlands was repeated. This cluster is characterised by a high index of energy consumption per capita and a high index of GHG emission per capita. II. CONCLUSIONS: It must be emphasised that the period 2001-2010 is connected with the transition process of the electric energy and gas sectors in the European Union. The process is also associated with the introduction of the 1st Climate-Energy Package in the European Union. What is more, the changes will be continued on account of the efforts at building an Energy Union as well as the implementation of the so-called 2nd Climate-Energy Package. Of particular significance is also the increase in the import dependence of the European Union, given the declining reserves of energy resources. Moreover, the objectives of the "green energy policy" will be giving rise to the increasing energy efficiency and the growing share of renewable energy sources in energy production, which may constitute a factor limiting the import dependence. Thus, it should be posited that in the long term we will be witnessing a homogenisation of indexes, e.g. the index of energy intensity. These processes may result in the tendency for changes towards the model of the "energy culture," which Z. Łucki and W. Misiak have termed a "Scandinavian culture," that is one characterised by the following features: (1) a development of RES, (2) a low consumption of coal, (3) a low index of GHG emission, (4) a considerable energy consumption, (5) a low energy intensity, (6) a heightened environment- and energy-consciousness. By way of comparing the analyses for 2011 and for 2001, based on the k-means clustering method, it must be stressed that Belgium, Luxembourg and the Netherlands hold steady in the cluster (Cluster VI), whereby they abide by the roles played by the features earlier ascribed to them. A measure of stability can also be observed in the case of Spain, France, Italy, Great Britain and Germany (Clusters I and V). Noteworthily, Sweden has been eliminated from the group (despite lowering the scale of the first three indexes). The distinctive feature of Eastern European countries is the high scale of the energy intensity index, as viewed against the backdrop of Clusters I and IV. Yet, some tendency towards stirring of the scale of energy intensity index is to be observed in this scope. A transformation of the energy structure will also prove quite a challenge here. Poland can serve as an example, whereby coal will continue to be the country's main electric energy carrier for the next 30 years. The comparative analysis featuring in the text is limited, and so it does not address all the issues concerned with the correlations between the presented "energy cultures." The work sets out to verify the results of the research into the existence of "energy cultures" in the European Union, as presented by A. Pach-Gurgul, Z. Łucki and W. Misiak as well as P. Tapio and his research team. Still, the greatest emphasis has been laid on the proposals made by A. Pach-Gurgul, for it was her publication as well as the selection of indexes and research tools included therein that proved to be an inspiration for the present text. It should also be noted that the object of analysis in the text does not embrace a discussion of the legitimacy of employing specific methods for clustering. ; The main objective of the text is to present an analysis that points to the existence of special "energy cultures" in the European Union. The comparative analysis encompassing the results of previous research into "energy cultures" employs statistical methods, i.e. a cluster analysis (Ward's clustering method and k-means clustering method). The main sections of the text address: (1) the concept and examples of "energy cultures," (2) a methodology of analysis, (3) a selection of indexes characterising "energy cultures," (4) an attempt at grouping the European Union member states with the aid of clustering, (5) conclusions. With a view to making the research problem more specific, the present text features the following questions: (1) Is the claim that the European Union manifests special "energy cultures" legitimate?, (2) Did the decade of 2001-2011 witness changes in the field of the European Union "energy cultures," as earlier recognised by the literature?

This paper provides evidence on the impacts of agricultural productivity on employment growth and structural transformation of non-farm activities. To guide the empirical work, this paper develops a general equilibrium model that emphasizes distinctions among non-farm activities in terms of tradable-non-tradable and the formal-informal characteristics. The model shows that when a significant portion of village income is spent on town/urban goods, restricting empirical analysis to the village sample leads to underestimation of agriculture's role in employment growth and transformation of non-farm activities. Using rainfall as an instrument for agricultural productivity, empirical analysis finds a significant positive effect of agricultural productivity growth on growth of informal (small-scale) manufacturing and skilled services employment, mainly in education and health services. For formal employment, the effect of agricultural productivity growth on employment is found to be largest in the samples that include urban areas and rural towns compared with rural areas alone. Agricultural productivity growth is found to induce structural transformation within the services sector with employment in formal/skilled services growing at a faster pace than that of low skilled services.

Sont d'abord rappelées quelques définitions liées à l'effet de serre et au rôle des arbres et de la forêt vis-à-vis de cet effet. Sont ensuite étudiés le rôle direct du bois dans le stockage du carbone et la réduction du taux de gaz carbonique dans l'atmosphère, avec présentation de résultats d'études de modélisation, et l'effet indirect que permet le bois en tant qu'économiseur d'énergie fossile. Si les effets direct et indirect des produits bois sur l'effet de serre sont une réalité positive, l'augmentation effective de la part des marchés du bois dans la construction pour accélérer cette réduction est une autre chose qui dépend du comportement des consommateurs, et sur ce dernier point d'importantes actions de communication doivent se poursuivre.

Among the various natural hazards, mass movements (MM) are probably the most damaging to the natural and human environment in the Mediterranean countries, including Lebanon which represents a good case study of mountainous landscape. Although affecting vast areas in the country, the phenomenon was not studied at regional scale, and related maps are still lacking. Therefore, this research deals with the use of remote sensing and geographic information system (GIS) techniques in studying MM in Lebanon. In this context, the first part reviews existing knowledge on the topics of mass movements (MM) specifically in the Mediterranean region, and defines research gaps. It exposes the diverse types of MM, their magnitudes, the causative agents and their bad consequences. It clarifies confusions related to MM-terms (hazard, susceptibility, risk, etc.), and compares the efficiencies of the most used methods for MM susceptibility/hazard zonation. It includes also a statement on remote sensing and GIS benefits and constraints in mass movement studies, pointing out possible ways of research. The second part is dedicated to the detailed description of the study area "the Mediteranean slopes of central to north Lebanon" within Lebanon. Physical/morphodynamic and socioeconomic characteristics of the area are exposed, as well as the natural hazards, MM events, their socio-economic impacts and mitigation measures. All previous studies about MM hazard in Lebanon are reviewed. The studied area, extending from the Mediterranean coast to around 3000 m elevation, covers ~36% of the total area of Lebanon. It represents the geoenvironmental diversity of this country in terms of geology, soil, hydrography, land cover and climate. It is characterized by problematic human activities (e.g., chaotic urban expansion, artificial recharge of groundwater, overgrazing, forest fire) enhancing environmental decline and inducing MM, with minimal government control. The third part compares the applicability of different satellite sensors (Landsat TM, IRS, SPOT4) and preferred image processing techniques (False Color Composite "FCC", Pansharpen, Principal component analysis "PCA", Anaglyph) for the mapping of MM recognized as landslides, rock/debris falls and earth flows. Results from the imagery have been validated by field surveys and analysis of IKONOS imagery (1 m) acquired in some locations witnessing major MM during long periods. Then, levels of accuracies of detected MM from satellite imageries were plotted. This study has demonstrated that the anaglyph produced from the two panchromatic stereo-pairs SPOT4 images remains the most effective tool setting the needed 3-D properties for visual interpretation and showing maximum accuracy of 69%. The PCA pan-sharpen Landsat TM-IRS image gave better results in detecting MM, among other processing techniques, with maximum accuracy level of 62%. The errors in interpretation fluctuate not only according to the processing technique, but also due to the difference in MM type. They are minimal once 3D anaglyph SPOT4 is considered, varying between 31% (landslides), 36% (rock and debris falls) and reaching 46% in the case of earth and debris flows. The fourth part explores relationships between MM occurrence and different factor terrain parameters. Parameters expressed by: 1- preconditioning factors, like: elevation, slope gradient, slope aspect, slope curvature, lithology, proximity to fault line, karst type, distance to quarries, soil type, distance to drainage line, distance to water sources, land cover/use, and proximity to roads, and 2- triggering MM factors, like: rainfall quantity, seismic events,floods and forest fires, were correlated with MM using GIS-approaches. This study indicates, depending on bivariate remote sensing and GIS statistical correlations (Kendall Tau-b correlation), that lithology is the most influencing on MM occurrence, having the highest correlation with other parameters (i.e. 7 times correlated at 1% level of significance and 3 times at 5%). It also shows that statistical correlations to mass movements exist best between parameters at the following decreasing order of importance: soil type/distance to water sources (acting similarly on MM occurrence), karst/distance to quarries/land cover-use, proximity to faults, slope gradient/proximity to roads/floods, seismic events, elevation/slope aspect/forest fires. These correlations were verified and checked through field observations and explained using univariate statistical correlations. Therefore, they could be extrapolated to other Mediterranean countries having similar geoenvironmental conditions. The fifth part proposes a mathematical decision making method - Valuing Analytical Bi- Univariate (VABU) that considers two-level weights for mapping MM susceptibility/hazard (1:50,000 cartographic scale) within the study area. The reliability of this method is examined through field surveys and depending on a GIS comparison with other statistical methods - Valuing accumulation Area (VAA) (depending on one weight level) and Information Value (InfoVal) (requiring detailed measurements of MM areas). Three susceptibility maps were derived using preconditioning parameters, while hazard maps were produced from triggering ones. The coincidence values of overlapping susceptibility maps were found to be equal to 47.5% (VABU/VAA), 54% (VABU/InfoVal) and 38% (VAA/InfoVal). The agreement between hazard maps showed closer values than susceptibility ones, oscillating between 36.5% (VAA/InfoVal), 39% (VABU/VAA), and 44 % (VABU/InfoVal). Field verification indicates that the total precision of the produced susceptibility maps ranges from 52.5% (VAA method), 67.5% (InfoVal method) and 77.5% (VABU method). This demonstrates the efficiency of our method, which consequently can be adopted for predictive mapping of MM susceptibility/hazard in other areas in Lebanon and may be easily extrapolated using the functional capacities of GIS. The sixth part predicts the geographic distribution and volume of block falls (m3) across the study area using GIS decision-tree modelling. Such mapping was unavailable in Lebanon, but also in many other countries putting effort on landslide research rather than other types of MM. Several decision-tree models were developed using (1) all terrain parameters, (2) topographic parameters only, (3) geologic parameters only, and adopting various processing techniques (pruned and unpruned trees). The best regression tree model combined all parameters and explained 80% of the variability in field blocks falls' measurements. The unpruned model built using four geological parameters (lithology, soil type, proximity to fault line, and karst type) seems also interesting, classifying 68% of block falls and referring to a small amount of input data (4 parameters). The produced predictive quantitative block falls' map at 1:50,000 appears extremely useful for decision-making, helping adoption of mitigation measures to reduce the occurrence of harmful block falls. The seventh part focuses on monitoring MM activity through integrating space borne radar data and Global Positioning System (GPS) techniques. ERS radar imageries were processed using InSAR and permanent scatters techniques. The analysis showed difficulties in detecting ground deformations due to MM. Nevertheless, the analysis is still in its preliminary stage and future planned work will take into consideration other manipulating procedures for detecting the displacements. On the other hand, a GPS installation in Hammana area; one of the Lebanese villages lying in a major landslide, was conducted. Two campaigns were raised, but results are still lacking since there is not enough data accumulation. More observations are still needed to build up a comprehensive picture on the direction and velocity of the movement. ; Parmi les aléas naturels, les mouvements de terrain (MT) sont probablement les plus nuisibles à l'environnement naturel et humain, notamment dans les pays méditerranéens, incluant le Liban qui représente un bon cas d'étude de région montagneuse. Ce phénomène n'a pas été étudié à l'échelle régionale bien qu'il affecte de vastes zones dans ce pays, et les cartes d'aléa manquent encore. La recherche présentée ici est consacrée à l'utilisation des techniques de télédétection et des systèmes d'informations géographiques (SIG), pour l'étude des MT au Liban. La première partie passe en revue les connaissances existantes sur le thème des mouvements de terrain (MT), plus spécifiquement dans la région méditerranéenne, et définit les lacunes de recherche. Elle expose les divers types existants de MT, leurs magnitudes, les agents causatifs, et leurs effets. Elle clarifie la terminologie utilisée pour les MT (aléa, susceptibilité, risque, etc.), et compare les méthodes les plus utilisées pour la cartographie de l'aléa/susceptibilité aux MT. Elle présente aussi un état des avantages et problèmes de la télédétection et du SIG dans les études de mouvements de terrain, en insistant sur les voies possibles de recherche. La deuxième partie est consacrée à la description détaillée de la région d'étude qui couvre les versants méditerranéens du nord du Liban central. Les caractéristiques physiques/morphodynamiques et socio-économiques de cette région sont exposées, ainsi que les aléas naturels, les événements de MT, les impacts socio-économiques et les mesures de conservation. Toutes les études sur l'aléa MT au Liban sont revisitées. La région d'étude, s'étendant de la côte méditerranéenne jusqu'à 3000 m d'altitude, couvre à peu près 36 % de la superficie totale du Liban. Elle est représentative de la diversité géo-environnementale de ce pays en termes de géologie, sol, hydrographie, occupation du sol et climat. Elle se caractérise par des activités humaines problématiques (par exemple une expansion urbaine chaotique, la recharge artificielle des eaux souterraines, un surpâturage, des incendies de forêt), accroissant la dégradation de l'environnement et induisant les MT, avec un contrôle gouvernemental minime. La troisième compare l'efficacité de différents capteurs satellitaires à résolutions variées (Landsat TM, IRS, SPOT4) et diverses techniques de traitement d'image (composition colorée, fusion, analyse en composantes principales ACP, vision stéréoscopique) pour la détection visuelle des mouvements de terrain classés en glissements, éboulements de blocs rocheux et de débris, et coulées de boue. Les résultats ont été validés sur le terrain et en analysant des images IKONOS (1 m) acquises en certaines localités menacées par des MT sur de longues périodes. Ensuite, les niveaux de précision de la détection des MT à partir des images satellitaires ont été calculés. Cette étude a montré que l'anaglyphe produit à partir des images panchromatiques stéréo SPOT4 reste l'outil le plus efficace grâce aux caractéristiques 3D jouant un rôle essentiel dans l'interprétation visuelle et montrant un niveau de précision (pourcentage des MT détectés et vérifiés sur le terrain) maximal de 69 %. De plus, l'image de fusion Landsat TM-IRS, calculée par ACP, fournit des résultats de détection des MT meilleurs que les autres techniques, avec un niveau de précision de 62 %. Les erreurs d'interprétation fluctuent non seulement en fonction de la technique de traitement utilisée, mais aussi en fonction des types de MT. Elles sont minimes quand l'anaglyphe (3D) SPOT4 est pris en considération, variant de 31 % (glissements), 36 % (éboulements de blocs rocheux et de débris) à 46 % dans le cas des coulées de boue. La quatrième partie explore les relations entre l'occurrence de MT et les paramètres du terrain. Ces paramètres sont: 1- les facteurs de prédisposition, comme l'altitude, la pente en gradient, l'aspect de pente, la courbure de pente, la lithologie, la proximité aux failles, le type de karst, la distance aux carrières, le type de sol, la distance aux réseaux de drainage, la distance aux sources, l'occupation/utilisation du sol et la proximité aux routes, et 2- les facteurs déclenchants, comme la quantité de pluies, les événements sismiques, les inondations et les incendies de forêt, qui ont été corrélés avec les MT en utilisant les approches SIG. Cette étude montre, en se basant sur les corrélations statistiques bi-variées satellitaires et SIG (corrélation Kendal Tau-b), que la lithologie est ce qui influence le plus l'occurrence des MT, puisqu'elle a la corrélation la plus élevée avec les autres paramètres (7 fois corrélée à un niveau de signification de 1 %, et 3 fois à 5 %). Elle montre aussi que les corrélations statistiques entre ces paramètres et les mouvements de terrain existent suivant l'ordre d'importance décroissant suivant : type de sol/distance aux sources (agissant de manière similaire sur l'occurrence des MT), karst/distance aux carrières/occupation/utilisation du sol, proximité aux failles, gradient de pente/proximité aux routes/inondations, événements sismiques, altitude/aspect de pente/incendies de forêt. Ces corrélations sont vérifiées sur le terrain et expliquées en utilisant des corrélations statistiques uni-variées. Par conséquent, elles peuvent être extrapolées à d'autres pays méditerranéens caractérisés par des conditions géoenvironnementales similaires. La cinquième partie propose une méthode mathématique décisionnelle (méthode analytique bi-univariée d'évaluation ou "Valuing Analytical Bi-Univariate (VABU)") qui considère deux niveaux de pondération pour la cartographie de l'aléa/susceptibilité des MT (échelle 1/50000) dans la région d'étude. La fiabilité de cette méthode est examinée sur le terrain et en la comparant avec d'autres méthodes statistiques - Valuing accumulation Area (VAA) (un seul niveau d'évaluation) and Information Value (InfoVal) (nécessitant des mesures détaillées des MT). Trois cartes de susceptibilité sont dérivées en utilisant les facteurs conditionnant l'occurrence des MT, tandis que les cartes d'aléa sont produites à partir des facteurs déclenchants. Les valeurs de coïncidence de superposition des cartes de susceptibilité sont de 47,5 % (VABU/VAA), 54 % (VABU/InfoVal) et 38% (VAA/InfoVal), respectivement. L'accord entre les cartes d'aléas montre des valeurs proches de celles des cartes de susceptibilité, variant entre 36,5 % (VAA/InfoVal), 39 % (VABU/VAA), et 44 % (VABU/InfoVal). La validation sur le terrain indique que la précision totale des cartes de susceptibilité produites varie entre 52,5% (méthode VAA), 67,5% (méthode InfoVal) et 77,5% (méthode VABU). Cela démontre l'efficacité de notre méthode qui peut être adoptée pour une cartographie prédictive de l'aléa et de la susceptibilité des MT dans d'autres régions au Liban, et peut être aussi aisément extrapolée en utilisant les capacités fonctionnelles du SIG. La sixième partie prédit la distribution géographique et le volume des blocs rocheux (m3) dans la région d'étude en utilisant la modélisation suivant un arbre décisionnel. Une telle cartographie est indisponible au Liban, mais aussi dans d'autres pays qui portent plutôt leur effort sur la recherche des glissements plutôt que les autres types de MT. Plusieurs modèles d'arbres décisionnels ont été développés en utilisant, (1) tous les paramètres de terrain, (2) les paramètres topographiques uniquement, (3) les paramètres géologiques, et en adoptant plusieurs techniques de traitement. Le meilleur arbre de régression combine tous les paramètres et explique 80 % de la variabilité dans les mesures des blocs rocheux sur le terrain. Le modèle construit en utilisant les quatre paramètres géologiques (lithologie, type de sol, proximité aux failles et type de karst) parait aussi intéressant car il classe 68 % des blocs rocheux tout en se référant à un petit nombre de données d'entrée (4 paramètres). La carte produite de 'prédiction quantitative des blocs rocheux' à l'échelle du 1/50 000 apparait extrêmement utile pour la décision, aidant à l'adoption des mesures de conservation afin de réduire l'occurrence de movements nuisibles de blocs rocheux. La septième partie s'intéresse à la surveillance de l'activité des MT à travers l'intégration des données spatiales radar et des techniques GPS (Système de positionnement global). Les données radar ERS sont traitées en utilisant les techniques InSAR et des réflecteurs permanents. Cette analyse montre des difficultés pour la détection des MT. Cependant, elle est jusqu'à présent préliminaire, et un plan de travail futur prendra en considération d'autres traitements pour la détection des déplacements. D'un autre côté, une installation GPS a été effectuée dans la région de Hammana, un village libanais menacé par un grand glissement. Deux campagnes ont été rassemblées, mais les résultats manquent encore puisqu'il n'y a pas des données accumulées suffisantes. Plus d'observations sont nécessaires afin de construire une représentation compréhensive de la direction et de la vitesse du mouvement.