Yanyun Luo

Landform classification using soil data and remote sensing in northern Ordos Plateau of China

Landform classification is commonly done using topographic altitude only. However, practice indicates that locations at a same altitude may have distinctly different landforms, depending on characteristics of soils underneath those locations. The objectives of this study were to: 1) develop a landform classification approach that is based on both altitude and soil characteristic; and 2) use this approach to determine landforms within a watershed located in northern Ordos Plateau of China. Using data collected at 134 out of 200 sampling sites, this study determined that D10 (the diameter of soil particles 10% finer by weight) and long-term average soil moisture acquired in 2010, which can be estimated at reasonable accuracy from remote sensing imagery, can be used to represent soil characteristics of the study watershed. Also, the sampling data revealed that this watershed consists of nine classes of landforms, namely mobile dune (MD), mobile semi-mobile dune (SMD), rolling fixed semi-fixed dune (RFD), flat sandy land (FD), grassy sandy land (GS), bedrock (BR), flat sandy bedrock (FSB), valley agricultural land (VA), and swamp and salt lake (SW). A set of logistic regression equations were derived using data collected at the 134 sampling sites and verified using data at the remaining 66 sites. The verification indicated that these equations have moderate classification accuracy (Kappa coefficients

Influences of landform as a confounding variable on SOM-NDVI association in semiarid Ordos Plateau

\hat K

Multivariate properties of extreme precipitation events in the Pearl River basin, China: magnitude, frequency, timing and related causes

> 43%). The results revealed that the dominant classes in the study watershed are FD (36.3%), BR (27.0%), and MD (23.5%), while the other six types of landforms (i.e., SMD, RFD, GS, FSB, VA, and SW) in combination account for 13.2%. Further, the landforms determined in this study were compared with the classes presented by a geologically-based classification map. The comparison indicated that the geologically-based classification could not identify multiple landforms within a class that are dependent upon soil characteristics.

PREDICTED SOIL EROSION RESPONSE TO ANTHROPOGENIC ACTIVITY AND CLIMATE CHANGE IN AN ARID TYPICAL STEPPE WATERSHED

Soil organic matter (SOM) plays an important role in maintaining vegetation cover and thus mitigating land erosion of fragile terrestrial ecosystems such as in the Northern Ordos Plateau of China (NOPC). However, little information is available on whether and how SOM varies spatially as an intrinsic characteristic of landform in NOPC. The objective of this study was to examine the spatial associations of SOM with landform and vegetation cover. The study was conducted in a 23,000-km 2 area within NOPC because this area has landforms of mobile dunes (MD), flat dunes (FD), grassy sandy land (GSL), flat sandy bedrocks (FSB), and swamps and salt lakes (SW), which are typical landforms in semiarid ecosystems. SOM was determined using a standard laboratory analysis method for 5 cm topsoil samples collected at 72 locations across the study area. In addition, the 250 m Multitem- poral Moderate Resolution Imaging Spectroradiometer (MODIS) imageries taken in the period from August 2006 to August 2010 were used to extract Normalized Difference Vegetation Index (NDVI) which in turn was used as the surrogate of vegetation cover. Classic and geostatistical methods were used to compare SOM concentration across different landforms. The results indicated that an area with a greater value for NDVI (i.e. better vegetation cover) tended to have a higher SOM concentration regardless of the landform types. However, the association between SOM and NDVI varied from one landform to another. The SW and GSL had a highest SOM concentration, while MD had a lowest concentration. For the study area as a whole and the FD, GSL, and MD, SOM was found to be the sole function of NDVI, whereas, for the FSB, SOM was influenced by several intrinsic variables, namely ground surface altitude, slope, and aspect, as well as NDVI. SOM for the SW landform was found to be a function of NDVI. Furthermore, SOM and NDVI exhibited a consistent spatial pattern of increasing from north to south and from west to east. The highest SOM concentration of 3.5% occurred along an east-westward belt, which is adjacent to water pathways, in the mid part of the study area.

Trend and extreme occurrence of precipitation in a mid-latitude Eurasian steppe watershed at various time scales

Daily precipitation/temperature data collected at 74 weather stations across the Pearl River basin of China (PRBC), for the years 1952-2013 were used to analyze extreme precipitation (EP) processes at annual and seasonal scales in terms of precipitation magnitude, occurrence rates and timing. Peak-over-Threshold (POT) sampling, Modified Mann-Kendall (MMK) trend tests and Poisson regression model (PRM) were utilized in this study. Causes driving the observed statistical behaviors of EP were investigated, focusing particularly on the impacts of temperature change and the El Nino-Southern Oscillation (ENSO). EP events, which occur mainly during April and September, are most frequent in June. At an annual scale they are subject to relatively even inter-annual distributions during the wet season. Significant trends were observed in the magnitude, frequency and timing of EP events during the dry seasons, although no such trends were seen during the wet seasons. Seasonal shifts in EP can easily trigger sudden flood or drought events and warming temperatures and ENSO events also have significant impacts on EP processes across the PRBC, as reflected by their increased magnitude and frequency in the western PRBC and decreased precipitation magnitudes in the eastern PRBC during ENSO periods. These results provide important evidence of regional hydrological responses to global climate changes in terms of EP regimes in tropical and subtropical zones.

Predicted NPP spatiotemporal variations in a semiarid steppe watershed for historical and trending climates

Steppe grassland is one of the most precious green-vegetation renewable resources in Inner Mongolia of northern China as well as all over the world. Not only the grassland is the material basis for animal husbandry but it also plays an important role in sustaining vulnerable steppe ecosystem. However, one noticeable problem is that large areas of steppe (particularly typical) grassland are being degraded as a result of inappropriate anthropogenic activities (e.g., overexploitation and overgrazing) and climate change, which in turn has become a key constraint to the sustainability of grassland agriculture. For instance, 90% of the steppe grassland in China has exhibited somewhat degree of degradation. Previous studies indicated that climate in the Inner Mongolia steppe region has been displaying a warming trend, accompanied by a clear increase in air temperature during winter and serious drought in spring. Also, previous studies indicated that a grazing intensity of GIj = 1.2 or greater would cause sustainability problems for steppe grassland. Herein, grazing intensity is defined as the ratio of the aboveground alive dry biomass per unit ungrazed area to that per unit grazed area provided that these two areas are similar in terms of hydrologic conditions and soil properties. However, while hydrology alteration and its subsequent soil erosion are two direct factors of inducing grassland degradation, few studies examined how these two factors respond to anthropogenic activities and climate change. Further, it is unclear how erosion of the top 10 to 20 cm calcic castanozem soil affects and is affected by degradation of grasses. The objectives of this study were to: 1) propose a conceptual ecohydrologic model; and 2) use the model to examine interrelations among hydrology alteration, soil erosion, and grassland degradation in a typical steppe watershed located in northeastern China. The results indicated that for the study watershed, the maximum interaction between wind and water erosion would occur at a soil moisture level of 20 to 30%. For a given vegetation coverage, soil erosion was predicted to increase by 1.7 cm yr -1 per 1% decrease of soil moisture. The increase of soil erosion rate per 1% decrease of vegetation coverage would be larger for a lower soil moisture level than that for a higher moisture level and can be as high as 0.5 cm yr -1 . Because climate change will result in lowered soil moisture and inappropriate anthropogenic activities could drastically reduce vegetation coverage, it is expected that soil erosion would be elevated if no measure is taken. The possible measures may include grazing rotation and water table management.