Desertification and Sustainable Development of the Heihe River Basin in Arid Northwestern China

The Heihe River Basin of northwestern China is one of several areas severely affected by desertification. This article outlines the status of desertification in this basin. There are mainly 5 types of desertification in the Heihe River Basin, namely soil and water erosion, sandy desertification, soil aridization, soil salinization and vegetation degradation. Among the 5 types of desertification, the main desertification type is sandy desertification with an area of 10 771.97 km2; Second type is soil salinization with an area of 10 591.82 km2; Next to the soil salinization is the type of soil and water erosion with an area of 5 747.68 km2 and the other types of desertification in the Heihe River Basin are soil aridization with just area of 1 369.96 km2 and vegetation degradation type with an area of 1 490.48 km2 respectively. Both natural and man-made factors are responsible for the causes of desertification development, among which the latter is the main driving force for desertification in the basin.

Integrated modeling environment and a preliminary application on the Heihe River Basin, China

Environmental and water issues are essentially complex interdisciplinary problems. Multiple models from different disciplines are usually integrated to solve those problems. Integrated modeling environment is an effective technical approach to model integration. Although a number of modeling environments worldwide are available, they cannot meet current challenges faced. Their old-fashion designs and original development purposes constrain their possible applications to the domain of hydrologic or land surface modeling. One of the challenges is that we intend to link knowledge database or ontology system to the modeling environment in order to make the modeling support more intelligent and powerful. In this paper, we designed and implemented an integrated modeling environment (HIME) for hydrological and land surface modeling purpose in a much extendable, efficient and easy use manner. With such design, a physical process was implemented as a module, or component. A new model can be generated in an intuitive way by linking module icons together and establishing their relationships. Following an introduction to the overall architecture, the designs for module linkage and data transfer between modules are described in details. Using XML based meta-information, modules in either source codes or binary form can be utilized by the environment. As a demonstration, with the help of HIME, we replaced the evaporation module of TOPMODEL with the evapotranspiration module from the Noah land surface model which explicitly accounts for vegetation transpiration. This example showed the effectiveness and efficiency of the modeling environment on model integration.

Relationship between sand-dust weather and water dynamics of desert areas in the middle reaches of Heihe River

Sand-dust weather has become an international social-environmental issue of common concern, and constitutes a serious threat to human lives and economic development. In order to explore the responses of natural desert sand and dust to the dynamics of water in desertification, we extracted long-term monitoring data related to precipitation, soil water, groundwater, and sand-dust weather. These data originated from the test stations for desertification control in desert areas of the middle reaches of the Heihe River. We used an algorithm of characteristic parameters, correlations, and multiple regression analysis to establish a regression model for the duration of sand-dust weather. The response char-acteristics of the natural desert sand and dust and changes of the water inter-annual and annual variance were also examined. Our results showed： （1） From 2006 to 2014 the frequency, duration, and volatility trends of sand-dust weather obviously increased, but the change amplitudes of precipitation, soil water, and groundwater level grew smaller. （2） In the vegetative growth seasons from March to November, the annual variance rates of the soil moisture content in each of four studied layers of soil samples were similar, and the changes in the frequency and duration of sand-dust weather were similar. （3） Our new regression equation for the duration of sand-dust weather passed the R test, F test, and t test. By this regression model we could predict the duration of sand-dust weather with an accuracy of 42.9%. This study can thus provide technological support and reference data for water resource management and re-search regarding sand-dust weather mechanisms.

Simulation of hydrological processes of mountainous watersheds in inland river basins: taking the Heihe Mainstream River as an example

The hydrological processes of mountainous watersheds in inland river basins are complicated.It is absolutely significant to quantify mountainous runoff for social,economic and ecological purposes.This paper takes the mountainous watershed of the Heihe Mainstream River as a study area to simulate the hydrological processes of mountainous watersheds in inland river basins by using the soil and water assessment tool(SWAT)model.SWAT simulation results show that both the Nash–Sutcliffe efficiency and the determination coefficient values of the calibration period(January 1995 to December 2002)and validation period(January 2002 to December 2009)are higher than 0.90,and the percent bias is controlled within±5%,indicating that the simulation results are satisfactory.According to the SWAT performance,we discussed the yearly and monthly variation trends of the mountainous runoff and the runoff components.The results show that from 1996 to 2009,an indistinctive rising trend was observed for the yearly mountainous runoff,which is mainly recharged by lateral flow,and followed by shallow groundwater runoff and surface runoff.The monthly variation demonstrates that the mountainous runoff decreases slightly from May to July,contrary to other months.The mountainous runoff is mainly recharged by shallow groundwater runoff in January,February,and from October to December,by surface runoff in March and April,and by lateral flow from May to September.