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Benefit Assessment And Spatial Prediction Of Green Manuring

Posted on:2017-05-29Degree:DoctorType:Dissertation
Country:ChinaCandidate:Z M ZhouFull Text:PDF
GTID:1223330512450418Subject:Land use and IT
Abstract/Summary:PDF Full Text Request
Green manuring is an important measure to promote the sustainable development of agriculture in China, and it could increase soil fertility and accordingly crop growth and productivity, optimize the farmland ecological environment, and reduce energy consumption and greenhouse gas emission. Although considerable research has been done on evaluation of the effectiveness of the green manuring, a systematical system for evaluation of the green manuring planting is still absent to date which affects the development of the green manure planting in China. In addition, there is still lack of a reasonable prediction for the spatial pattern of the green manuring planting. In order to address these issues, through using ecology and environmental economics theory, first we discussed and analyzed the comprehensive impacts of green manuring planting on farmland ecosystems after growing green manure by considering the service function and environmental burden that farmland ecosystems produced, and constructed an evaluation system on the effectiveness of growing and using green manure. Then we introduced land use change simulation and forecasting model to explore the feasibility of the model for predicting green manure spatial distribution at county scale. Finally, we developed a management and development decision making system for green manure on county scale. Results of this study provide methods for assessment of green manure comprehensive benefits at regional scale, ecological compensation, and spatial prediction of planting. The main results and conclusions are in the following.Firstly, we evaluated the Ecosystem Service of introducing green manure crop to farm land before the crop planting. Based on the Agro-Ecosystem Service Appraisal Theory, we used methods from ecological economics to develop a systematic model to evaluate the ecological service value of practicing the planting model of winter green manure and spring maize rotation in North China Plain in farm land. This model has considered the unique properties of green manuring and it estimates the ecological services value by considering influence of green manure on five ecological services function (i.e., crop production, gas regulation, water conservation, soil conservation, and soil nutrient accumulation). Then we used the model to estimate ecological services value of practicing rotation planting of Vicia villosa Roth or Orychophragmus violaceus and spring maize in North China Plain with using planting spring maize only as the control model. Results show that the ecological services value of rotation of Vicia villosa Roth and Orychophragmus violaceus with spring maize were 71,449 and 68,962 Yuan per hectare, respectively. Compared to planting spring maize only, the introduction of Vicia villosa Roth and Orychophragmus violaceus increased ecological services value by 23.45% and 19.15%, respectively. Planting green manure crops had greatest benefit on gas regulation which accounted for 60.84%~61.13% of the total ecological services value. Planting green manure crops had the second greatest benefit on crop production which accounted for 19.92%~20.30% of the total values. The other benefits of planting green manure crops follows the order of water conservation> soil nutrient accumulation> soil conservation. There were different effects of introduction of Vicia villosa Roth and Orychophragmus violaceus on soil nutrient accumulation. Specifically, planting Vicia villosa Roth mainly increases available phosphorus and soil organic matter, whereas planting Orychophragmus violaceus mainly increases alkali-hydro nitrogen. The above results show that the developed model is effective to estimate the benefits of planting green manure crops in fallow farm land in winter, which have provided theoretical basis for decision making about the planting green manure.Second, we further investigate effects of green manure planting during the process of filed ecosystem production on saving energy and pollution control. We designed three kinds of Crop rotation mode, including Orychophragmus violaceus rotation spring maize mode, Vicia villosa Roth rotation spring maize mode, and Orychophragmus violaceus Mixture Vicia villosa Roth rotation spring maize in North China. Then this thesis comprehensively compared the resource consumption and pollutant emissions with using the above three crop rotation modes using Life Cycle Assessment method, in which the farmland area that can produce 1 t corn was used as the evaluation functional unit. The resource consumption and pollutant emissions specifically considered energy consumption, water consumption, land resource consumption, global warming, acidification, eutrophication and soil toxicity. The results show that, chemicals, oil, and pesticide production that is necessary for the rotation model of winter green manure with spring maize during the agricultural materials phase can cause energy consumption and potential global warming. In the farming stage, the field production activities such as site preparation, fertilization, irrigation, and spraying can cause the potential environmental acidification, eutrophication and soil toxicity. Excess nitrogen fertilizer is the main reason for the eutrophication and acidification of the environment. The potentially soil toxicity is mainly caused by the excessive inputs of pesticides and fertilizer.Compared with the conventional spring maize planting, the three rotation models of winter green manure with spring maize can save energy, and reduce greenhouse gas emissions, water eutrophication, acidification. Therefore, green manuring in fallow land could decrease the demand of crop for fertilizers which directly reduce the pollution caused by the loss of farmland nitrogen and phosphorus, and indirectly reduce resource consumption and pollutant emissions during agricultural production processes. Consequently, green manuring can effectively reduce the farmland system environmental impact of the life cycle. Third, we estimated the influence of green manure growing on improving farmland ecosystem service function and energy conservation. We developed an assessment indicator system for green manure planting by using AHP (Analytic Hierarchy Process) method and by considering soil fertility, soil and water conservation, pollution control and revenue. As a demonstration, we made a comprehensive analysis on Orychophragmus violaceus spring maize rotation mode, Vicia villosa Roth spring maize rotation mode, and Orychophragmus violaceus Mixture Vicia villosa Roth spring maize rotation pattern in the north of China. Results show that the benefits of three models of rotation of winter green manure with spring Maize are significantly greater than that of traditional spring maize monoculture mode mainly by enhancing water and soil conservation, controlling pollutants, and improving fertility. The benefits of the three models follow the order of Orychophragmus violaceus Mixture Vicia villosa Roth spring maize rotation pattern (with a score of 20.9)> Orychophragmus violaceus rotation spring corn mode (18.3)> Vicia villosa Roth spring maize rotation mode (16.9). The above results show that the benefits of all the three rotation planting models of winter green manure with spring maize mode can meet the ecological requirements at the region, with the rotation pattern of Orychophragmus violaceus Mixture Vicia villosa Roth with spring maize got highest benefits, which is thus preferentially recommended.Fourth, by considering the fact that there is still lack of prediction models for spatial distribution of green manure planting in China to date, we used the CLUE-S (Conversion of Land Use and its Effects at Small regional extent) model, which is originally developed for simulation of land use changes, to predict spatial distribution of green manure in croplands and orchards in 2020 in Pinggu District, Beijing, China. Four land use types for planting or not planting green manure are classified and the future land use dynamics, mainly croplands and orchards are considered in the prediction. Two scenarios were used to predict the spatial distribution of green manure in 2020 using the data of 2011:the promotion of green manure planting in orchards (scenario 1) and the promotion of simultaneous green manure planting in orchards and croplands (scenario 2). The ROC coefficient and Kappa indices, which validate the effective of the CLUE-S model in the prediction, show that the predictions were generally accurate. The obtained spatial distribution of green manure in the two scenarios is in the following. In scenario 1, green manure is mainly located in the orchards of the middle and southern regions of Dahuashan, the western and southern regions of Wangxinzhuang, the middle region of Shandongzhuang, the eastern region of Pinggu, and the middle region of Xiagezhuang. In scenario 2, green manure planting is mainly distributed in orchards in middle region of Wangxinzhuang and most croplands in Daxinzhuang, southern Pinggu, northern Xiagezhuang, and Mafang.Finally, to meet the demand of green manure development and decision making in China, we developed a decision making system for guiding green manure development and management at county scale by referencing the above research of green manure comprehensive benefit evaluation and by using spatial layout prediction method. This system was developed using C # in Microsoft Visual Studio 2010 with combination with ArcGIS component development technology. The system has the functions of (1) county green manure development decisions, (2) green manure knowledge query, (3) map management modules, and (4) evaluating the green manure planting potential and temporal and spatial layout. In general, the system can provide decision support for the county’s green manure development and management in China.
Keywords/Search Tags:Green Manure, Ecosystem Service, Life Cycle Assessment, Benefit Assessment, Spatial Prediction, Decision Making System
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