Possible Biogeophysical Effects of Cultivated Land Conversion in Northeast China in 2010–2030

There will be substantial cultivated land change in China as the society strives to meet the growing food demands, which will greatly influence the future climate. This study analyzed the possible biogeophysical effects of cultivated land change on the climate in Northeast China during 2010–2030 on the basis of simulation with the Weather Research and Forecast (WRF) model. Scenario analysis was first carried out on the possible changing trends of cultivated land. Then the climate effects of the cultivated land change were analyzed on the basis of the simulation with the WRF model. The simulation results indicate that the total cultivated land area in Northeast China will decrease during 2010–2030, mainly converting into urban and built-up land and forests due to the urbanization and governmental policies. Besides, the cultivated land change will lead to the increase of the sensible heat flux in the regions where a lot of cultivated land will change into urban and built-up land, while it will make the latent heat flux increase in the regions where the cultivated land will be mainly converted into forests through influencing the evapotranspiration. All these results can provide theoretical support for implementing the future land management in Northeast China

A review of historical reconstruction methods of land use/land cover

Understanding long-term human-environment interactions requires historical reconstruction of past land-use and land-cover changes. Most reconstructions have been based primarily on consistently available and relatively standardized information from historical sources. Based on available data sources and a retrospective research, in this paper we review the approaches and methods of the digital reconstruction and analyze their advantages and possible constraints in the following aspects: (1) Historical documents contain qualitative or semi-quantitative information about past land use, which also usually include land-cover data, but preparation of archival documents is very time-consuming. (2) Historical maps and pictures offer visual and spatial quantitative land-cover information. (3) Natural archive has significant advantages as a method for reconstructing past vegetation and has its unique possibilities especially when historical records are missing or lacking, but it has great limits of rebuilding certain land-cover types. (4) Historical reconstruction models have been gradually developed from empirical models to mechanistic ones. The method does not only reconstruct the quantity of land use/cover in historical periods, but it also reproduces the spatial distribution. Yet there are still few historical land-cover datasets with high spatial resolution. (5) Reconstruction method based on multiple-source data and multidisciplinary research could build historical land-cover from multiple perspectives, complement the missing data, verify reconstruction results and thus improve reconstruction accuracy. However, there are challenges that make the method still in the exploratory stage. This method can be a long-term development goal for the historical land-cover reconstruction. Researchers should focus on rebuilding historical land-cover dataset with high spatial resolution by developing new models so that the study results could be effectively applied in simulations of climatic and ecological effects

The impacts of climate change and agricultural activities on water cycling of Northern Eurasia

The ecosystems in Northern Eurasia (NE) are important due to their vast land coverage, high rate of observed and projected warming, and the potential feedbacks they can cause on the global climate system. To understand the impacts of climate change and agricultural activities on water cycling in NE, I analysed a variety of datasets and conducted series of studies by applying a combination of modeling, in-situ observations and remote sensing data, uncertainty analysis, and model-data fusion.^ Long-term unique in-situ measurements on soil moisture across multiple stations and discharge records at the outflow basins in Northern China (NC) provide us robust evidence to assess the trends of soil moisture and discharge in this region (Chapter 2). NC overlaps with NE and is one of the hot-spots experiencing the most severe water shortage in the world. Declines in soil moisture and stream flow detected via in-situ measurements in the last three decades indicate that water scarcity has been exacerbated. Multiple linear regression results indicate that intensification of agricultural activities including increase in fertilizer use, prevalence of water-expensive crops and cropland expansion appear to have aggravated these declines in this region.^ Scarce evapotranspiration (ET) measurements make ET estimation via model a necessary step for better regional-scale water management. Penman–Monteith based algorithms for plant transpiration and soil evaporation were introduced into the Terrestrial Ecosystem Model (TEM) to calculate ET (Chapter 3). I then examined the response of ET and water availability to changing climate and land cover on the Mongolian Plateau during the 21st century. It is shown that use of the Penman–Monteith based algorithms in the TEM substantially improved ET estimation on the Mongolia Plateau. Results show that regional annual ET varies from 188 to 286 mm yr−1 – with an increasing trend – across different climate change scenarios during the 21st century. Meanwhile, the differences between precipitation and ET suggest that the available water for human use will not change significantly during the 21st century. In addition, analyses also suggest that climate change is more important than land cover change in determining changes in regional ET.^ Improvement in the accuracy of ET estimation by introducing Penman–Monteith based algorithms into the TEM motivated me to further improve the model representation of ET processes. I further modified the TEM to incorporate more detailed ET processes including canopy interception loss, ET (evaporation) from wetland surfaces, wetlands and water bodies, and snow sublimation to examine spatiotemporal variation of ET in NE from 1948 to 2009 (Chapter 4). Those modifications lead to substantial enhancement in the accuracy of estimation of ET and runoff. The consideration of snow sublimation substantially improved the ET estimates and highlighted the importance of snow in the hydrometeorology of NE. The root mean square error of discharge from the six largest watersheds in NE decreased from 527.74 km 3 yr-1 to 126.23 km3 yr-1. Meanwhile, a systematic underestimation of river discharge after 1970 indicates that other water sources or dynamics not considered in the model (e.g., melting glaciers, permafrost thawing and fires) or bias in the precipitation forcing may also be important for the hydrology of the region.^ To better understand the possible causes of systematic bias in discharge estimates, I examined the impacts of forcing data uncertainty on ET and runoff estimation in NE by driving the modified TEM with five widely-used forcing data sets (Chapter 5). Estimates of regional ET vary between 263.5-369.3 mm yr-1 during 1979-2008 depending on the choice of forcing data, while the spatial variability of ET appears more consistent. Uncertainties in ETforcing propagate as well to estimates of runoff. Independent of the forcing dataset, the climatic variables that dominate ET temporal variability remain the same among all the five TEM simulated ET products. ET is dominated by air temperature in the north and by precipitation in the south during the growing season, and solar radiation and vapour pressure deficit explain the dynamics of ET for the rest of the year. While the Climate Research Unit (CRU) TS3.1 dataset of the University of East Anglia appears as a better choice of forcing via our assessment, the quality of forcing data remains a major challenge to accurately quantify the regional water balance in NE

Vegetation Dynamics Revealed by Remote Sensing and Its Feedback to Regional and Global Climate

This book focuses on some significant progress in vegetation dynamics and their response to climate change revealed by remote sensing data. The development of satellite remote sensing and its derived products offer fantastic opportunities to investigate vegetation changes and their feedback to regional and global climate systems. Special attention is given in the book to vegetation changes and their drivers, the effects of extreme climate events on vegetation, land surface albedo associated with vegetation changes, plant fingerprints, and vegetation dynamics in climate modeling