Yingkui Li

Lake variations in response to climate change in the Tibetan Plateau in the past 40 years

The Qinghai-Tibetan Plateau plays an important role in global climate and environmental change and holds the largest lake area in China, with a total surface area of 36,900 km2. The expansion and shrinkage of these lakes are critical to the water cycle and ecological and environmental systems across the plateau. In this paper, surface areas of major lakes within the plateau were extracted based on a topographic map from 1970, and Landsat MSS, TM and ETM+ satellite images from the 1970s to 2008. Then, a multivariate correlation analysis was conducted to examine the relationship between the changes in lake surface areas and the changes in climatic variables including temperature, precipitation, evaporation, and sunshine duration. Initial results suggest that the variations in lake surface areas within the plateau are closely related to the warming, humidified climate transition in recent years such as the rise of air temperature and the increase in precipitation. In particular, the rising temperature accelerates melting of glaciers and perennial snow cover and triggers permafrost degradation, and leads to the expansion of most lakes across the plateau. In addition, different distributions and types of permafrost may cause different lake variations in the southern Tibetan Plateau.

Glacial valley cross-profile morphology, Tian Shan Mountains, China

Abstract The morphology of glacial valley cross-sections can be described in terms of power law ( y = ax b ) or quadratic equations ( y = a + bx + cx 2 ) fitted to empirical data. The quadratic solution provides a more robust way of describing the morphology of glacial valley cross-sections, whereas the power law has more potential in understanding the cross-sectional shapes and their evolution. These two functions are used to study the cross-sectional morphology of glacial valleys in the middle and western Tian Shan Mountains and to discuss the comparison with fluvial channels. The major conclusions are: (1) Power law equation parameters ( a and b ) are sensitive to the origin selection with larger sensitivity in vertical and A ( A =ln a ) values. Conversely, c values of the quadratic equation are more stable regardless of different origins selected. (2) Hirano and Aniya [Earth Surf. Processes Landforms 13 (1988) 707–716] suggested two characteristic patterns in the relationship between the power law exponent, b , and the valley form ratio, FR . However, glacial valleys in these areas do not fit the Rocky Mountain model for b–FR values described by Hirano and Aniya for alpine glacial valleys. This indicates that this Rocky Mountain model cannot be applied to all alpine glacial areas. (3) The c values of the quadratic equation represent a curvi-linear trend with its corresponding FR s. At the same time, power law parameters ( A and b ) fit a closed linear relationship both from these areas and others in the published literature. (4) The cross-sectional shapes of glacial valleys show clear differences with fluvial channels by comparing A–b values of glacial valleys with the hydraulic geometry of fluvial channels. This implies that the A–b relationship and the variation range of b values (commonly with 1.5–2.5) may be helpful to differentiate valleys formed by different processes.

Patterns and potential drivers of dramatic changes in Tibetan lakes, 1972-2010.

Most glaciers in the Himalayas and the Tibetan Plateau are retreating, and glacier melt has been emphasized as the dominant driver for recent lake expansions on the Tibetan Plateau. By investigating detailed changes in lake extents and levels across the Tibetan Plateau from Landsat/ICESat data, we found a pattern of dramatic lake changes from 1970 to 2010 (especially after 2000) with a southwest-northeast transition from shrinking, to stable, to rapidly expanding. This pattern is in distinct contrast to the spatial characteristics of glacier retreat, suggesting limited influence of glacier melt on lake dynamics. The plateau-wide pattern of lake change is related to precipitation variation and consistent with the pattern of permafrost degradation induced by rising temperature. More than 79% of lakes we observed on the central-northern plateau (with continuous permafrost) are rapidly expanding, even without glacial contributions, while lakes fed by retreating glaciers in southern regions (with isolated permafrost) are relatively stable or shrinking. Our study shows the limited role of glacier melt and highlights the potentially important contribution of permafrost degradation in predicting future water availability in this region, where understanding these processes is of critical importance to drinking water, agriculture, and hydropower supply of densely populated areas in South and East Asia.

Towards a GIS assessment of numerical ice-sheet model performance using geomorphological data

A major difficulty in assimilating geomorphological information with ice-sheet models is the lack of a consistent methodology to systematically compare model output and field data. As an initial step in establishing a quantitative comparison methodology, automated proximity and conformity analysis (APCA) and automated flow direction analysis (AFDA) have been developed to assess the level of correspondence between modelled ice extent and ice-marginal features such as end moraines, as well as between modelled basal flow directions and palaeo-flow direction indicators, such as glacial lineations. To illustrate the potential of such an approach, an ensemble suite of 40 numerical simulations of the Fennoscandian ice sheet were compared to end moraines of the Last Glacial Maximum and the Younger Dryas and to glacial lineations in northern Sweden using APCA and AFDA. Model experiments evaluated in this manner were ranked according to level of correspondence. Such an approach holds considerable promise for optimizing the parameter space and coherence of ice-flow models by automated, quantitative assessment of multiple ensemble experiments against a database of geological or glaciological evidence.

Impacts of Urbanization on Surface Runoff of the Dardenne Creek Watershed, St. Charles County, Missouri

Accurately documenting urban growth and evaluating its hydrological impact are of great interest for urban planning and water/land resource management. St. Charles County, a suburb of St. Louis, Missouri, has undergone significant urban expansion in recent decades. Rapid urban sprawl in the Dardenne Creek watershed within the county has had a profound influence on surface runoff. We examined the patterns of land use/land cover (LULC) change in this watershed using Landsat TM/ETM+ imagery in 1982, 1987, 1991, 1999, and 2003. Calibrated with the observed hydrological data in 2003, a Long-Term Hydrologic Impact Assessment (L-THIA) model was used to evaluate the effect of LULC change on surface runoff. Results indicated a rapid increase of urban areas in the watershed, from 3.4% in 1982 to 27.3% in 2003, dominated by changes in the lower portion of the watershed close to the metropolitan area. Model simulations suggest >70% increase in average direct runoff in the watershed from 1982 to 2003, and the runoff increase is highly correlated with urban expansion. This work helps raise awareness of the scale of hydrologic impacts of urbanization in this watershed, and provides a simple calibrated tool for local planners to assess potential hydrological impacts of future planning and development activities.

Long-term effects of land use/land cover change on surface runoff in urban areas of Beijing, China

Abstract The objective of this paper is to present a case study to derive land use/land cover (LULC) maps and investigate the long-term effects of LULC change on surface runoff in the fast urbanizing Beijing city. The LULC maps were derived from Landsat TM/ETM+ imagery (acquired in 1992, 1999, 2006, and 2009) using support vector machine method. A long-term hydrologic impact assessment model was applied to assess the impact of LULC change on surface runoff. Results indicated that the selected study area experienced rapid urbanization from 1992 to 2009. Because of urbanization, from 1992 to 2009, modeled runoff increased 30% for the whole area and 35% for the urban portion. Our results also indicated that the runoff increase was highly correlated with urban expansion. A strong relationship ( R 2 = 0.849 ) was observed between the impervious surface percent and the modeled runoff depth in the study area. In addition, a strong positive relationship was observed between runoff increase and percentage of urban areas ( R 2 = 0.997 for the whole area and R 2 = 0.930 for the urban portion). This research can provide a simple method for policy makers to assess potential hydrological impacts of future urban planning and development activities.

Comparing predicted and observed spatial boundaries of geologic phenomena: Automated Proximity and Conformity Analysis applied to ice sheet reconstructions

Comparing predicted with observed geologic data is a central element of many aspects of research in the geosciences, e.g., comparing numerical ice sheet models with geomorphic data to test ice sheet model parameters and accuracy. However, the ability to verify predictions using empirical data has been limited by the lack of objective techniques that provide systematic comparison and statistical assessment of the goodness of correspondence between predictions of spatial and temporal patterns of geologic phenomena and the field evidence. Much of this problem arises from the inability to quantify the level of agreement between straight or curvilinear features, such as between the modeled extent of some geologic phenomenon and the field evidence for the extent of the phenomenon. Automated Proximity and Conformity Analysis (APCA) addresses this challenge using a system of Geographic Information System-based buffering that determines the general proximity and parallel conformity between linear features. APCA results indicate which modeled output fits empirical data, based on the distance and angle between features. As a result, various model outputs can be sorted according to overall level of agreement by comparison with one or multiple features from field evidence, based on proximity and conformity values. In an example application drawn from glacial geomorphology, APCA is integrated into an overall model verification process that includes matching modeled ice sheets to known marginal positions and ice flow directions, among other parameters. APCA is not limited to ice sheet or glacier models, but can be applied to many geoscience areas where the extent or geometry of modeled results need to be compared against field observations, such as debris flows, tsunami run-out, lava flows, or flood extents.

Identifying patterns of correspondence between modeled flow directions and field evidence: An automated flow direction analysis

Comparison of numerical model output that predicts spatial flow patterns against field observations is a necessity within several areas of the geosciences. However in many cases these comparisons are qualitative or relative in nature. Automated flow direction analysis (AFDA) is a new method designed to provide a systematic comparison between modeled flow patterns and field observations, with particular focus on two-dimensional linear features representing flow directions of natural phenomena. By subtracting vector output of time-dependent models from field-observed directions, the resultant mean residual and variance of the offset between these data sets can be used to identify patterns of correspondence and variation between model-predicted directions and field observations. The technique is demonstrated by comparison of modeled basal ice flow directions of the Fennoscandian Ice Sheet with observed lineations mapped in Northern Sweden. In this example, the analysis provides an effective means to quantitatively validate the modeled basal thermal and flow regime with observed glacial lineations. The technique has potential applications in a wide range of flow vector direction comparisons in the geosciences, for example lava flow, landslides, aeolian and fluvial processes.

A revised automated proximity and conformity analysis method to compare predicted and observed spatial boundaries of geologic phenomena

Quantitative assessment of the level of agreement between model-predicted and field-observed geologic data is crucial to calibrate and validate numerical landscape models. Application of Geographic Information Systems (GIS) provides an opportunity to integrate model and field data and quantify their levels of correspondence. Napieralski et al. [Comparing predicted and observed spatial boundaries of geologic phenomena: Automated Proximity and Conformity Analysis (APCA) applied to ice sheet reconstructions. Computers and Geosciences 32, 124-134] introduced an Automated Proximity and Conformity Analysis (APCA) method to compare model-predicted and field-observed spatial boundaries and used it to quantify the level of correspondence between predicted ice margins from ice sheet models and field observations from end moraines. However, as originally formulated, APCA involves a relatively large amount of user intervention during the analysis and results in an index to quantify the level of correspondence that lacks direct statistical meaning. Here, we propose a revised APCA approach and a more automated and statistically robust way to quantify the level of correspondence between model predictions and field observations. Specifically, the mean and standard deviation of distances between model and field boundaries are used to quantify proximity and conformity, respectively. An illustration of the revised method comparing modeled ice margins of the Fennoscandian Ice Sheet with observed end moraines of the Last Glacial Maximum shows that this approach provides a more automated and statistically robust means to quantify correspondence than the original APCA. The revised approach can be adopted for a wide range of geoscience issues where comparisons of model-predicted and field-observed spatial boundaries are useful, including mass movement and flood extents.

Human Impacts on Soil Erosion Identified Using Land-Use Changes: A Case Study From The Loess Plateau, China

Human impacts on soil erosion are generally reflected in land-use changes. Thus, identifying the characteristics of land-use changes associated with their driving forces has great potential for evaluating regional soil-erosion variations and the impacts of human activities, especially for regions where soil-erosion data are scarce. A case study from Zhifanggou, a small watershed in the hilly area of the Loess Plateau, China, is conducted through a systematic analysis of temporal variations in land-use patterns from 1938 to 1999, combined with local soil-erosion observations. Multiple series of land-use data indicate three distinct stages of change in land-use patterns and conversions matching three different periods of soil erosion: (1) pristine conditions before 1938; (2) severe degradation between 1958 and 1978; and (3) gradual rehabilitation from 1978 to 1999. The trends and styles of land-use changes and soil erosion are primarily driven by regional policy, with abrupt changes during policy transformations and stability between policy changes. Other socioeconomic factors also contribute to land-use changes during periods of stable policy. This suggests that policy should be established cautiously, because an unsuitable strategy may lead to greater degradation in ecological quality than other factors.