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This paper, using a revised Penman-Monteith model, computed the terrestrial surface humidity index of the Loess Plateau (China) based on climatic factors of monthly mean temperature, maximum temperature, minimum temperature, relative humidity, precipitation, wind speed and sunshine duration observed on the plateau from 1961 to 2008. The temporal-spatial distribution, anomaly distribution and sub-regional temporal variations of the terrestrial surface dry and wet conditions were analyzed as well. The results showed a decreasing trend in the annual average surface humidity from the southeast to the northwest in the research area. Over the period of 1961-2008, an aridification tendency appeared sharply in the central interior region of the Loess Plateau, and less sharply in the middle part of the region. The border region showed the weakest tendency of aridification. It is clear that aridification diffused in all directions from the interior region. The spatial anomaly distribution of the terrestrial surface dry and wet conditions on the Loess Plateau can be divided into three key areas: the southern, western and eastern regions. The terrestrial annual humidity index displayed a significantly descending trend and showed remarkable abrupt changes from wet to dry in the years 1967, 1977 and 1979. In the above mentioned three key areas for dry and wet conditions, the terrestrial annual humidity index exhibited a fluctuation period of 3-4 years, while in the southern region, a fluctuation period of 7-8 years existed at the same time.

Based on information distribution and diffusion method theory and combined with the standardized precipitation index and relative meteorological yield data, meteorological factors and social factors were comprehensively considered to assess the vulnerability of maize (Zea mays) to drought. The probability distribution curve of meteorological drought degree (MDD) and relative meteorological yield in the eastern part of Northwest China (Gansu, Ningxia and Shaanxi) from 1978 to 2016 were obtained, using a two-dimensional normal information diffusion method to construct the vulnerability relationship between MDD and relative meteorological yield. The drought vulnerability curve of maize in the study area was obtained. The probability distribution of MDD was multiplied by the fragility curve and summed to obtain the multi-year average risk. The MDD probability distribution curve showed that the probability of moderate drought in Shaanxi was relatively high, followed by Gansu and Ningxia. The probability distribution of Gansu was more discrete. The probability of strong meteorological drought in Ningxia was high, followed by Shaanxi and Gansu. Probability distribution of relative meteorological yield for maize in Gansu Province was highly discrete, with thick tailings, large uncertainties, and more extreme values, which were strongly affected by meteorological conditions, followed by Shaanxi and Ningxia. Taking meteorological drought as the cause and maize damage as the result, the vulnerability relationship between MDD and drought damage was obtained. With an increased MDD, the relative meteorological yield of maize gradually declined. From the average value, when MDD was less than −2.60, the relative meteorological yield of maize was reduced within 15%; when MDD was greater than −2.60, the relative meteorological yield of maize increased within 10%. When the degree of meteorological drought exceeded −2.2, maize was most vulnerable to drought in Shaanxi followed by Ningxia and Gansu. When meteorological drought was less than −2.2, maize was most vulnerable to drought in Shaanxi followed by Gansu and Ningxia. The expected values of relative meteorological production in Gansu, Ningxia, and Shaanxi were 1.36%, 2.48%, and −1.76%, respectively; therefore, Shaanxi had the highest maize drought risk, followed by Gansu and Ningxia. This research had a clear physical background and clear risk connotations. The results provide a data foundation and a theoretical basis for drought disaster reduction for maize in the study area.