999 resultados para North Hampton
Resumo:
Chinese Academy of Sciences [KZCX2-YW-315-2]; National Natural Science Foundation of China [40701021, 40625002]; National Key Technology R&D Program of China [2007BAC03A01]
Resumo:
Sustainable water use is seriously compromised in the North China Plain (NCP) due to the huge water requirements of agriculture, the largest use of water resources. An integrated approach which combines the ecosystem model with emergy analysis is presented to determine the optimum quantity of irrigation for sustainable development in irrigated cropping systems. Since the traditional emergy method pays little attention to the dynamic interaction among components of the ecological system and dynamic emergy accounting is in its infancy, it is hard to evaluate the cropping system in hypothetical situations or in response to specific changes. In order to solve this problem, an ecosystem model (Vegetation Interface Processes (VIP) model) is introduced for emergy analysis to describe the production processes. Some raw data, collected by investigating or observing in conventional emergy analysis, may be calculated by the VIP model in the new approach. To demonstrate the advantage of this new approach, we use it to assess the wheat-maize rotation cropping system at different irrigation levels and derive the optimum quantity of irrigation according to the index of ecosystem sustainable development in NCP. The results show, the optimum quantity of irrigation in this region should be 240-330 mm per year in the wheat system and no irrigation in the maize system, because with this quantity of irrigation the rotation crop system reveals: best efficiency in energy transformation (transformity = 6.05E + 4 sej/J); highest sustainability (renewability = 25%); lowest environmental impact (environmental loading ratio = 3.5) and the greatest sustainability index (Emergy Sustainability Index = 0.47) compared with the system in other irrigation amounts. This study demonstrates that application of the new approach is broader than the conventional emergy analysis and the new approach is helpful in optimizing resources allocation, resource-savings and maintaining agricultural sustainability.
Resumo:
A probabilistic soil moisture dynamic model is used to estimate the soil moisture probability distribution and plant water stress of irrigated cropland in the North China Plain. Soil moisture and meteorological data during the period of 1998 to 2003 were obtained from an irrigated cropland ecosystem with winter wheat and maize in the North China Plain to test the probabilistic soil moisture dynamic model. Results showed that the model was able to capture the soil moisture dynamics and estimate long-term water balance reasonably well when little soil water deficit existed. The prediction of mean plant water stress during winter wheat and maize growing season quantified the suitability of the wheat-maize rotation to the soil and climate environmental conditions in North China Plain under the impact of irrigation. Under the impact of precipitation fluctuations, there is no significant bimodality of the average soil moisture probability density function.