Development of a Regional Regression Model for Estimating Annual Runoff in the Hailar River Basin of China

The Hailar River, a first-grade tributary of the Erguna River that borders China and Russia, is the main water source for the local industry and agriculture. However, because there are only 11 flow gauging stations and those stations cannot monitor all runoff paths, it is hard to directly use the existing flow data to estimate the annual runoffs from all subbasins of interest although such estimation is needed for utilization and protection of the water resources in the Hailar River. Thus, this study implemented an indirect approach (i.e., regional regression model) by correlating annual runoff with annual rainfall and water surface evaporation as well as hydrologic characteristics of the 11 subbasins monitored by the gauging stations. The study used 51 years (from 1956 to 2006) data. The results indicated a significant correlation (R2 > 0.87) between annual runoff and the selected subbasin characteristics and showed the model to be robust because the predicted runoffs for the validation period are compatible with the corresponding observed values. In addition, this model was used to estimate the annual runoffs for the subbasins that are not monitored by the 11 flow gauging stations, which adds new information to existing literature.

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

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-km2 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.

ORPOM model for optimum distribution of tree ring sampling based on the climate observation network

Tree ring dating plays an important role in obtaining past climate information.The fundamental study of obtaining tree ring samples in typical climate regions is particularly essential.The optimum distribution of tree ring sampling sites based on climate information from the Climate Observation Network(ORPOM model) is presented in this article.In this setup,the tree rings in a typical region are used for surface representation,by applying excellent correlation with the climate information as the main principle.Taking the Horqin Sandy Land in the cold and arid region of China as an example,the optimum distribution range of the tree ring sampling sites was obtained through the application of the ORPOM model,which is considered a reasonably practical scheme.

Effect of climatic change on surface environments in the typical region of Horqin Sandy Land

The town of Agura,a typical region in Horqin Sandy Land,was selected as the study area in this paper.Using 12 remote sensing images and climatic data from the past 20 years,the effects of climate change on surface environments were analyzed.The impact indices of climatic factors,along with their corresponding ranks,were used to characterize the responses of different types of surface environments to climate change.Results show that in the past 20 years,the surface environments of the study area have been deteriorating.Furthermore,there is a positive relationship between the changes in surface environments and those in climatic factors.Various climatic factors influence surface environments in different ways and at different levels.The most sensitive factor is relative humidity,followed by precipitation and evaporation.Overall,moisture is the key factor that affects the changes in surface environments of arid and semi-arid areas.