青藏高原河谷地区历史时期耕地格局重建方法探讨——以河湟谷地为例

doi:10.11820/dlkxjz.2015.02.009

摘要/Abstract

摘要：

青藏高原受其特殊自然地理环境条件的限制,耕地主要分布在自然环境条件相对优越的河谷地区,人为因素对耕地分布范围的作用和影响极其微弱,尤其是在历史时期生产力水平较低的前提下,耕地的空间分布主要取决于土地的宜垦程度。本文将影响青藏高原河谷地区耕地分布的因子按其性质分为限制性因子和非限制性因子,并以此为基础排除了高原河谷地区不适宜耕作的地区,在适宜耕作的地区根据土地的宜垦程度,按“先优后劣”的原则将历史时期的耕地数据分配到空间上。选取青藏高原农业发展历史悠久的河谷地区之一河湟谷地作为实例,重建该区1726年耕地空间格局。将重建结果与已有的M模型重建结果进行对比分析,两者重建的耕地在空间分布上呈现出一致性,但重建结果在垦殖范围与垦殖强度上存在一定的差异;M模型的重建主要是以现代耕地分布格局为基础重建,忽略了现代耕地空间分布受现代农业技术的影响;而本文模型则是从低生产力水平前提下影响历史时期耕地分布的因子出发,重建结果更具合理性。

关键词: 青藏高原, 河谷农业, 耕地空间分布, 网格化模型, 河湟谷地

Abstract:

Land use/cover change (LUCC) caused by human activities is not only one of the main causes that change the earth's natural ecosystem, but also one of the important factors that affect regional and global climate change. Thus it has become one of the core areas of the global environment change research. In recent years, research on reconstructing historical cropland spatial distribution has made important progress. Tibetan Plateau is an area that is fragile and sensitive to global climate change, particularly its river valleys. Analyzing historical land use/cover change of valleys on the Tibetan Plateau is of great significance to the understanding of regional and global environmental change. Existing research on land use/land cover change, however, rarely involves this region, due to the lack of historical data. This article attempts to fill this gap by exploring historical land use/cover change in the region. The vast Tibetan Plateau has a high altitude and cold climate, and is regarded as "the third pole of the earth," due to its special geographical position. Arable land area of the plateau is small although the total land area is large. The development of agriculture is restricted by the harsh natural environment. On the plateau weather condition in general is poor, but some valleys in the interior of the plateau have relatively low attitude and slope and high temperature and and fertile soil, so the cultivated land is mainly distributed in these valleys. The role of human factors on the distribution of cropland is very weak, especially in the historical period when agricultural productivity was low. Cropland distribution mainly depends on the suitability of land for reclamation, which is affected by a variety of natural environmental conditions. In this study, we first analyzed the relationship between environmental factors and the distribution of cultivated land in the Tibetan Plateau. We then divided the factors into limiting and non-limiting factor groups, and eliminated the areas that is not suitable for farming, and then distributed the cultivated land data based on suitability using a composite model. We reconstructed the cropland spatial distribution of the Yellow River-Huangshui River Valley in 1726 by using this method .The results show that this method is suitable for reconstructing historical cropland spatial distribution where agricultural productivity was low and the natural environment conditions strongly limited the development of agriculture.

Key words: Tibetan Plateau, valley agriculture, cropland spatial distribution, the grid model, Yellow River- Huangshui River Valley

罗静, 陈琼, 刘峰贵, 张镱锂, 周强. 青藏高原河谷地区历史时期耕地格局重建方法探讨——以河湟谷地为例[J]. 地理科学进展, 2015, 34(2): 207-.

Jing LUO, Qiong CHEN, Fenggui LIU, Yili ZHANG, Qiang ZHOU. Methods for reconstructing historical cropland spatial distribution of the Yellow River-Huangshui River valley in Tibetan Plateau[J]. PROGRESS IN GEOGRAPHY, 2015, 34(2): 207-.

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X_j	X_i
X_j	X₁	X₂	X₃	X₄	权系数	λ_Max=4.25CI=0.09
X₁	1	5	1/7	1/3	0.483
X₂	1/5	1	1/7	1/3	0.323
X₃	7	7	1	7	0.123
X₄	3	3	1/7	1	0.071
X_j	X_i
X_j	X₁	X₂	X₃	X₄	权系数	λ_Max=4.27CI=0.09
X₁	1	3	1/7	1/5	0.529
X₂	1/3	1	1/5	1/7	0.314
X₃	7	5	1	3	0.098
X₄	5	7	1/3	1	0.060
X_j	X_i
X_j	X₁	X₂	X₃	X₄	权系数	λ_Max=4.25CI=0.09
X₁	1	5	2	1/5	0.589
X₂	1/5	1	1/7	1/7	0.187
X₃	1/2	7	1	1/5	0.177
X₄	5	7	5	1	0.048

因子层	指标层	权重
非限制因子	坡向	0.07
	气候生产潜力	0.50
	土壤有机质含量	0.11
	人为因素的影响	0.32

县厅	垦殖率
县厅	模型	50%以上	50%~40%	40%~20%	20%~10%	10%以下
河湟谷地	M模型	0.037	0.018	0.094	0.169	0.683
河湟谷地	网格化模型	0.02	0.024	0.118	0.265	0.573
西宁县	M模型	0.071	0.032	0.13	0.222	0.546
西宁县	网格化模型	0.038	0.042	0.201	0.4	0.321
碾伯县	M模型	0.001	0.002	0.029	0.089	0.879
碾伯县	网格化模型	0	0	0.01	0.108	0.882
大通卫	M模型	0.029	0.016	0.131	0.219	0.605
大通卫	网格化模型	0.014	0.03	0.121	0.343	0.492
贵德厅	M模型	0	0	0	0.014	0.986
贵德厅	网格化模型	0	0	0	0	1
循化厅	M模型	0.039	0.027	0.131	0.198	0.604
循化厅	网格化模型	0.034	0.032	0.197	0.21	0.527

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