基于熵技术的半干旱地区土壤水分差异性分析

Difference of Soil Moisture Content in Semiarid Area Based on Entropy Technology

在安家坡流域6 a实测土壤水分数据的基础上,运用熵技术分析法,对农地、苜蓿、沙棘、荒坡4种不同土地利用下的土壤水分时空变异规律进行了分析。结果显示:土壤水分信息熵效用价值均体现自上而下不断减少的规律,浅层土壤水分信息熵效用价值最大;不同植被覆盖形式下土壤水分信息熵效用价值体现为:荒坡>沙棘>农地>苜蓿,并在60 cm和80 cm深处出现2个土壤水分信息熵增减的突变点;除沙棘灌丛外,7—8月土壤水分环境内部信息熵剧增,信息熵效用价值最低,土壤热容量急剧减少,从而影响到植物的正常生长。

Based on the data of soil moisture content in the Anjiapo Watershed in recent 6 years, the entropy technology was used to analyze the spatiotemporal variation of soil moisture content under four different land use types including farmland, alfalfa land, Hippophae rhamnoides land and barren slope land. The result showed that tile information entropy value of soil moisture content was decreased from topsoil to deeper soil layer, and it was the highest in shallow soil layer. Under different vegetation types, the information entropy value of soil moisture content was in an order of barren slope land 〉 Hippophae rhamnoides land 〉 farmland 〉 alfalfa land, and two abrupt change points occurred at soil depths of 60 cm and 80 cm. The information entropy of soil moisture content was sharply increased in July and August except in Hippophae rhamnoides land, the utility value of information entropy was the lowest, and the soil heat capacity was sharply reduced, thus the growth of vegetation was impacted.