Hailong He

Use of four drought indices for evaluating drought characteristics under climate change in Shaanxi, China: 1951–2012

Drought severity was simulated with four drought indices to examine the impacts of climate change on drought conditions in Shaanxi province over the period 1951 to 2012. The drought metrics analyzed were based on the original Palmer drought severity index (orPDSI), self-calibrated PDSI (scPDSI), the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). Both Thornthwaite (Thor) and Penman–Monteith (PM) parameterizations were used to calculate potential evapotranspiration (PET), and the differences between two PET estimators were studied. Nonparametric Mann–Kendall monotonic test was used to examine the trends of hydroclimatic data. Series of drought indices were compared at five meteorological stations with different climate characteristics, located in the north, central and south parts of Shaanxi province, respectively. Effects of climate change in drought conditions were investigated with hypothetical progressive precipitation decrease (−15xa0%) and temperature increase (2xa0°C). The results showed that there was discrepancy between PET estimated using the Thor and PM parameterization estimators, while the SPEI calculated with the two PET estimators are found to be similar. The SPEI has the combined advantages over the scPDSI and the SPI, considering the effect of temperature variability on drought severity and its multi-scalar characteristic, while scPDSI has an inherent approximately 12-month time scale. The Pearson’s correlation is used to compare the three pairs of drought indices combinations at different time scales. Under climate change conditions, the drought severity increases with the decline of precipitation and higher water demand as a result of the temperature increase based on the metrics of the scPDSI, the SPI and the SPEI.

Spatiotemporal variability of extreme precipitation in Shaanxi province under climate change

Extreme climate index is one of the useful tools to monitor and detect climate change. The primary objective of this study is to provide a more comprehensively the changes in extreme precipitation between the periods of 1954–1983 and 1984–2013 in Shaanxi province under climate change, which will hopefully provide a scientific understanding of the precipitation-related natural hazards such as flood and drought. Daily precipitation from 34 surface meteorological stations were used to calculated 13 extreme precipitation indices (EPIs) generated by the joint World Meteorological Organization Commission for Climatology (CCI)/World Climate Research Programme (WCRP) project on Climate Variability and Predictability (CLIVAR) expect Team on climate change Detection, Monitoring and Indices (ETCCDMI). Two periods including 1954–1983 and 1984–2013 were selected and five types of precipitation days (R10mm-R100mm) were defined, to provide more evidences of climate change impacts on the extreme precipitation events, and specially, to investigate the changes in different types of precipitation days. The EPIs were generated using RClimRex software, and the trends were analyzed using Mann-Kendall nonparametric test and Sen’s slope estimator. The relationships between the EPIs and the impacts of climate anomalies on typical EPIs were investigated using correlation and composite analysis. The mainly results include: 1) Thirteen EPIs, except consecutive dry day (CDD), were positive trends dominated for the period of 1984–2013, but the trends were not obvious for the period of 1954–1983. Most of the trends were not statistically significant at 5xa0% significance level. 2) The spatial distributions of stations that exhibited positive and negative trends were scattered. However, the stations that had negative trends mainly distributed in the north of Shaanxi province, and the stations that had positive trends mainly located in the south. 3) The percentage of stations that had positive trends had increased from the period of 1954–1983 to 1984–2013 for all the 13 EPIs except CDD, indicating the possible climate change impacts on extreme precipitation events. 4) The correlations between annual total wet-day precipitation (PRCPTOT) and other 12 EPIs varied for different indices and stations. The composite analysis found that El Niño Southern Oscillation (ENSO) exerted greater impacts on PRCPTOT than other EPIs and greater in the Guanzhong Plain (GZP) than Qinling-Dabashan Mountains (QDM) and Shanbei Plateau (SBP) of Shaanxi province.

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta’s smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen’s slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta’s sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30xa0years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982–2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for different period of year ecologists might focus on.

Development and application of the heat pulse method for soil physical measurements

Accurate and continuous measurements of soil thermal and hydraulic propertiesare required for environmental, Earth and planetary science, and engineering applications, but they are not practicallyobtained by steady-state methods. The heat pulse (HP) method is a transient method for determinationof soil thermal properties and a wide range of other physical properties in laboratory and field conditions. The HP method is based on the line-heat source solution of the radial heat flow equation. This literature review begins with a discussion of the evolution of the HP method and related applications, followed by the principal theories, data interpretation methods and their differences. Important factors for HP probe construction are presented. The properties determined in unfrozen and frozen soilsare discussed, followed by a discussion of limitations and perspectives for the application of this method. The paper closes with a brief overview of future needs and opportunities for further development and application of the HP method.

Correction to: A new and simple method for measuring in situ field-saturated hydraulic conductivity using a falling-head single cylinder

In the original publication of this article, the equationxa012 had a typographical error and has been incorrectly published online. Now the correct equation has been provided in this erratum.

A new and simple method for measuring in situ field-saturated hydraulic conductivity using a falling-head single cylinder

Hydraulic properties of soil play important roles in water and temperature regimes. Measuring hydraulic properties has been studied for decades in the laboratory and in the fields. In 1989 the Guelph Permeameter was introduced to measure in situ field-saturated hydraulic conductivity, Kfs, but it required an empirical constant. Until recently, no procedure had been introduced to in situ measure Kfs without an empirical constant. In this article, we proposed a new simple method to measure Kfs. Field and laboratory measurements for volcanic ash origin Kanto loam, loess, and Toyoura sand were taken using a metallic cylinder (30xa0cm long and 4.5xa0cm inner diameter) or a PVC cylinder (30xa0cm long and 5.0xa0cm inner diameter) installed into soil down to a 5xa0cm depth. Temporal changes in water depth or hydraulic head inside the cylinder were measured with a laser measure. Values of Kfs measured with this proposed method agreed well with saturated hydraulic conductivity measured in the laboratory for undisturbed soil cores. New analytical solution was derived for a future automated device for this purpose.