Search

Deep soil moisture is a highly important source of water for vegetation in the semiarid Loess Plateau of China, vegetation restoration reduced the deep soil moisture, but how to better quantify the impact of vegetation restoration on deep soil moisture is lack of certain understanding. To explore the impact exerted by different types of vegetation on deep layers of the soil moisture, the 0–10 m soil moisture content profile was measured before and after the rainy season in Armeniaca sibirica, Robinia pseudoacacia, Populus simonii, Pinus tabuliformis, Hippophae rhamnoides and in natural grassland in Wuqi County in Shannxi Province. These results showed that the highest soil moisture in the shallow layers (0–200 cm) was exhibited in the P. simonii forest, which was followed by that in the natural grassland. Both of these results were significantly higher than that those of the A. sibirica, P. tabuliformis, H. rhamnoides and R. pseudoacacia forests. The soil moisture in the deep layer (200–1000 cm) of the natural grassland was significantly higher than that of the other vegetation types. The annual precipitation that recharges the depth of soil moisture was the highest in natural grassland and the lowest in P. simonii. The inter-annual soil moisture replenishment is primarily affected by rainfall and vegetation types. Compared with the natural grassland, the CSWSD (the comparison of the soil moisture storage deficit) of different vegetation types varies. In the shallow soil layer, P. simonii is the lowest, and R. pseudoacacia is the highest. In the deep soil layer, R. pseudoacacia and P. simonii are the highest; H. rhamnoides is the second highest, and A. sibirica and P. tabuliformis are the lowest. These results indicate that vegetation restoration can significantly reduce the amount of water in the deep layers of the soil. In the future vegetation restoration, we suggest emphasizing natural development more strongly, since it can better maintain the local vegetation stability and soil moisture balance. [ABSTRACT FROM AUTHOR]

The loess hilly-gully region is a focus region of the “Grain for Green” program in China. Drought is the main problem in the study region. Precipitation and temperature are two indicators that directly characterize climatic drought. A thorough analysis of the precipitation, temperature and drought characteristics of the loess hilly-gully region can clarify the current water and heat conditions in the region to improve regional water resource management and provide a reliable reference for effectively improving water use efficiency. In this study, we fully analyzed the precipitation and temperature characteristics at 11 representative synoptic stations in the loess hilly-gully region over the period from 1957 to 2014 using a combination of trend-free pre-whitening, linear trend estimation, Spearman’s rho test, the Mann–Kendall (M-K) trend and abrupt change tests and wavelet analysis. The standardized precipitation evapotranspiration index was calculated and analyzed on different time scales. The following conclusions were drawn: (1) There were significant spatial differences and inter-annual variations in precipitation at the 11 synoptic stations in the study area between 1957 and 2014; the precipitation consistently decreased with fluctuations, and the extent of the decrease varied from a maximum of 17.74 mm/decade to a minimum of 2.92 mm/decade. Except for the downward trends of the autumn and winter mean temperatures at Hequ, the seasonal and annual mean temperatures at the stations showed upward trends, including highly significant upward trends. (2) Alternating drought and wetness occurred in the study area; the wet period mainly appeared in the 1960s, and the main dry period lasted from the late 20th century to 2012. There were fewer dry and wet years than normal years; however, the study area still showed a drying trend, and the severity of the drought was increasing. (3) The annual precipitation and annual mean temperature showed marked cyclical fluctuations at each synoptic station, and the first primary cycle was approximately 28 years. The seasonal precipitation and seasonal temperature showed different cycle lengths; the seasonal cycles of precipitation for spring, summer, autumn and winter were 10, 28, 10 and 26 years long, respectively, and the cycles of the temperature fluctuations for all four seasons were approximately 28 years long. [ABSTRACT FROM AUTHOR]

Precipitation is the only water supply and most important factor affecting vegetation growth on the slopes of semi-arid Loess Plateau of China. Based on precipitation data from 7 synoptic stations in the study area over the period 1957–2012, the trends of precipitation and standardized precipitation index (SPI) were analyzed by using linear regression, Mann−Kendall, and Spearman’s Rho tests at the 5% significance level. The results show that (1) the precipitation fluctuation of monthly precipitation was intense (coefficients of variation> 100%), and the drier years were recorded as 1965 and 1995 at all stations. (2) The significant change trend of different stations varied on different time scales: the Changwu station had a significant decreasing trend in April (−0.488 mm/year) and November (−0.249 mm/year), while Luochuan station was in April (−0.457 mm/year); Changwu station displayed a significant increasing trends in winter (0.220 mm/year) and a significant decreasing trends in spring (−0.770 mm/year). The significant decreasing trends in annual precipitation were detected at the Suide (−2.034 mm/year) and Yan’an (–2.129 mm/year) stations. (3) The SPI−12 series analysis suggests that the drought degree of Yulin and Changwu was the lowest and that of Hengshan was the highest among the 7 synoptic stations. [ABSTRACT FROM AUTHOR]

Abstract: The Stochastic generation of storm patterns is often necessary for driving process-based hydrological and ecological models. CLIGEN is the only weather generator being able to generate internal storm patterns. Its goodness needs to be evaluated for its proper application. This paper aims to find the advantages and limitations of CLIGEN on semiarid areas and provide references for custom-built weather generators for the Loess Plateau. The daily rainfall time series (1957–2002) and breakpoint rainfall data (more than 20 years) on six stations on the Loess Plateau were used to estimate input parameters for CLIGEN and to compare with CLIGEN-generated 50 years of storm data. Precipitation occurrence (wet day and dry day sequence) is well-simulated without significant difference across months and sites. Errors of monthly average number of wet days range from −0.67 to 1.08 days, standard deviations range from −1.19 to 0.76 days, and the distributions of continuous number of wet and dry days on the semiarid Loess Plateau are adequately simulated. Daily rainfall amount is not simulated as well as precipitation occurrence. The relative errors of average daily rainfall range from −12.93% to 8.64% and those of standard deviations range from −21.35% to 27.46%. During the rain seasons (May–September), among 30 month–location combinations, all the Mann–Whitney tests for the means passed, 47% for squared ranks tests rejected the null hypothesis of equality of standard deviations, and 73% for K–S test suggested that the generated and measured distributions of daily rainfall were different at 0.01 level of significance Three variables to describe internal storm patterns in CLIGEN are storm duration, relative peak intensity, and time to peak. Storm duration was not well-reproduced because none of squared ranks tests and K–S test passed at the significance level of 0.01. The frequency of short duration storms (<300 min) was over-predicted while frequency of long duration storms (400–1200 min) was significantly under-predicted. The distribution of maximum 5 min rainfall intensity (ip5) was well-simulated for four sites out of the six because all tests passed. However, generated maximum ip5 for all six sites are around 190 mm/h, which are much larger than the measured (70 to 150 mm/h). Ip30 is simulated better than ip5, suggesting that CLIGEN can reliably generate rainfall erosivity. Time to peak was well-simulated because all the tests passed with P values significantly greater than the significance level of P =0.01. Improvement for CLIGEN has to be made in terms of the daily rainfall simulation in rainfall-concentrated seasons and storm pattern generation in order to generate reliable rainfall time series on the Loess plateau. [Copyright &y& Elsevier]