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LOADEST is a program for estimating constituent loads in rivers and streams developed by the U.S. Geological Survey (USGS), but it does not have a Graphical User Interface (GUI) that facilitates processing of large amounts of data. Therefore, we present the LOAD ESTimation (LOADEST) Parallel Data Processing Interface (LPDPI). LPDPI is unique as it features an easy-to-use workflow for data download and water quality estimations for numerous stations and multiple constituents and is readily applicable to any station with both flow and water quality data available. LPDPI incorporates a parallel module for faster load estimation and can identify and fix errors that occur while running LOADEST by adjusting calibration and estimation data inputs. LPDPI also includes an extension to extract and filter LOADEST output to facilitate further data analysis and use of the data to calibrate hydrologic models. The tool is a standalone executable for Windows and can be readily used without any additional packages or software installation.
Jungang Gao; Michael J. White; Katrin Bieger; Jeffrey G. Arnold. Design and development of a Python-based interface for processing massive data with the LOAD ESTimator (LOADEST). Environmental Modelling & Software 2020, 135, 104897 .
AMA StyleJungang Gao, Michael J. White, Katrin Bieger, Jeffrey G. Arnold. Design and development of a Python-based interface for processing massive data with the LOAD ESTimator (LOADEST). Environmental Modelling & Software. 2020; 135 ():104897.
Chicago/Turabian StyleJungang Gao; Michael J. White; Katrin Bieger; Jeffrey G. Arnold. 2020. "Design and development of a Python-based interface for processing massive data with the LOAD ESTimator (LOADEST)." Environmental Modelling & Software 135, no. : 104897.
Accurate daily weather data are critical for hydrologic models simulating and predicting hydrologic processes. Many researchers have focused on the impacts of precipitation on hydrologic simulations, but few studies integrated both temperature and precipitation data for historical and forecast periods in hydrologic models and evaluated the weather data accuracy at national scale. This study evaluated four extracting methods (mean (MN), median (MD), centroid (CT), and area-weighted (AW) approaches) for summarizing weather data for sub-watersheds defined in a hydrologic model. Firstly, an optimized extracting method was used to develop a real-time HUC-12 (12-digit Hydrologic Unit Code) level dataset for the Conterminous United States. The hydrologic model with the CT weather data performed the best, followed by MN, AW, and then MD. Secondly, per this method, a real-time dataset including historical and forecast data at HUC-12 level across the conterminous United States was created. Last, continuous daily forecast data at national scale displayed that large forecast overestimations were usually observed in large forecast precipitation events over 20 mm. Simultaneously, there were large underestimations in small forecast precipitation events less than 5 mm. Forecast maximum temperature showed a more substantial bias than that minimum temperature, with the largest underestimation for the lower forecast maximum temperature less than 15 °C. With regard to data stability of the historical observed temperature data, provisional and early temperature data from Parameter-elevation Regressions on Independent Slopes Model (PRISM) in the most recent seven months are as reliable as the stable data that is subject to quality control measures before it replaces the provisional and early data. However, forecast data often included bias in the extreme weather conditions, such as heavy precipitation and scorching temperature. Forecast data, which is updated multiple times each day, was frequently subject to an opposite bias (trending toward less extreme values) in the presence of strong frontal systems presumably due to the exact location and speed of the front being difficult to predict. Fully processed weather data from this work will be published online to facilitate hydrologic modeling efforts in the US and inform users about the uncertainty in the forecast data.
Jungang Gao; Katrin Bieger; Michael J. White; Jeffrey G. Arnold. Development and accuracy assessment of a 12-digit hydrologic unit code based real-time climate database for hydrologic models in the US. Journal of Hydrology 2020, 586, 124817 .
AMA StyleJungang Gao, Katrin Bieger, Michael J. White, Jeffrey G. Arnold. Development and accuracy assessment of a 12-digit hydrologic unit code based real-time climate database for hydrologic models in the US. Journal of Hydrology. 2020; 586 ():124817.
Chicago/Turabian StyleJungang Gao; Katrin Bieger; Michael J. White; Jeffrey G. Arnold. 2020. "Development and accuracy assessment of a 12-digit hydrologic unit code based real-time climate database for hydrologic models in the US." Journal of Hydrology 586, no. : 124817.
Uncertainty in simulating hydrologic response to future climate is generally assumed to result from the combined uncertainties of the General Circulation Model (GCM), representative concentration pathway (RCP), downscaling method, and hydrologic model used. However, another source of uncertainty, the observed climate data source used to statistically downscale and bias-correct GCM projections, has largely been overlooked. This study assessed the shifts, variability, and uncertainty in streamflow simulation from three downscaling data sources (NCDC land-based weather stations, NEXRAD spatial grid, and PRISM spatial grid) relative to those introduced by six GCMs and three RCPs in west-central Kansas, U.S. Streamflow simulated by the Soil and Water Assessment Tool (SWAT) hydrologic model was found to be more sensitive to future precipitation than to maximum and minimum temperatures. The greatest uncertainty in simulated streamflow was associated with selection of the GCM. Uncertainty in simulated streamflow associated with the observed bias-correction data source (NCDC, PRISM, NEXRAD) was greater than with RCPs and was primarily related to uncertainty in precipitation. This study highlighted the importance of recognizing uncertainty from bias-correction data sources in representing future climate scenarios in hydrologic simulations.
Jungang Gao; Aleksey Y. Sheshukov; Haw Yen; Kyle R. Douglas-Mankin; Michael J. White; Jeffrey G. Arnold. Uncertainty of hydrologic processes caused by bias-corrected CMIP5 climate change projections with alternative historical data sources. Journal of Hydrology 2018, 568, 551 -561.
AMA StyleJungang Gao, Aleksey Y. Sheshukov, Haw Yen, Kyle R. Douglas-Mankin, Michael J. White, Jeffrey G. Arnold. Uncertainty of hydrologic processes caused by bias-corrected CMIP5 climate change projections with alternative historical data sources. Journal of Hydrology. 2018; 568 ():551-561.
Chicago/Turabian StyleJungang Gao; Aleksey Y. Sheshukov; Haw Yen; Kyle R. Douglas-Mankin; Michael J. White; Jeffrey G. Arnold. 2018. "Uncertainty of hydrologic processes caused by bias-corrected CMIP5 climate change projections with alternative historical data sources." Journal of Hydrology 568, no. : 551-561.
Alteration of flow regimes due to change in climate and its potential impact on habitat and species has become a major cause of concern for riverine ecosystems. Areas that are more vulnerable to such changes are semiarid river systems or regions experiencing intermittent flow and cyclic droughts. Although ecological changes are expected to occur with flow regime alterations, the biological changes cannot be predicted until the flow in such regions is analysed. This study addresses this concern by providing an analysis of flow for a semiarid river basin in the Central Great Plains from a 50 and 100-year projection climate data. The projected data for these two periods are then compared with 30-year historical data to determine changes in flow. Five major components of flow regime, magnitude, duration, and timing of annual extreme water conditions, frequency and duration of high and low pulses, and rate and frequency of water condition changes, were examined with respect to climate change for their impact on the ecology of the basin. This analysis strongly suggests that inter- and intra-annual changes in flow regimes will result in the intensified drying of the basin represented by the increased number of low flow periods followed by higher occurrences of high flow events of shorter duration with expected changes in climate.
S. Chatterjee; M.D. Daniels; A.Y. Sheshukov; J. Gao. Projected climate change impacts on hydrologic flow regimes in the Great Plains of Kansas. River Research and Applications 2018, 34, 195 -206.
AMA StyleS. Chatterjee, M.D. Daniels, A.Y. Sheshukov, J. Gao. Projected climate change impacts on hydrologic flow regimes in the Great Plains of Kansas. River Research and Applications. 2018; 34 (3):195-206.
Chicago/Turabian StyleS. Chatterjee; M.D. Daniels; A.Y. Sheshukov; J. Gao. 2018. "Projected climate change impacts on hydrologic flow regimes in the Great Plains of Kansas." River Research and Applications 34, no. 3: 195-206.
Model-based water quality assessments are an important informer of conservation and environmental policy in the U.S. The recently completed national scale Conservation Effects Assessment Project (CEAP) is being replicated using an improved model populated with new and higher resolution data. National assessments are particularly difficult as models must operate with both a very large spatial extent (the contiguous U.S.) while maintaining a level of granularity required to capture important small scale processes. In this research, we developed datasets to describe the hydrologic connectivity at the U.S. Geological Survey (USGS) 12-digit Hydrologic Unit Code (HUC-12) level. Connectivity between 86,000 HUC-12s as provided by the Watershed Boundary Dataset (WBD) was evaluated and corrected. We also detailed a method to resolve the highly detailed National Hydrography Dataset (NHD) stream segments within each HUC-12 into vastly simplified representative channel schemes suitable for use in the recently developed Soil and Water Assessment Tool + (SWAT+) model. This representative channel approach strikes a balance between computational complexity and accurate representation of the hydrologic system. These data will be tested in the upcoming CEAP II national assessment. Until then, all the WBD corrections and NHDPlus representative channel data are provided via the web for other researchers to evaluate and utilize.
Michael J. White; Katrin Beiger; Marilyn Gambone; Elizabeth Haney; Jeff Arnold; Jungang Gao. Development of a Hydrologic Connectivity Dataset for SWAT Assessments in the US. Water 2017, 9, 892 .
AMA StyleMichael J. White, Katrin Beiger, Marilyn Gambone, Elizabeth Haney, Jeff Arnold, Jungang Gao. Development of a Hydrologic Connectivity Dataset for SWAT Assessments in the US. Water. 2017; 9 (11):892.
Chicago/Turabian StyleMichael J. White; Katrin Beiger; Marilyn Gambone; Elizabeth Haney; Jeff Arnold; Jungang Gao. 2017. "Development of a Hydrologic Connectivity Dataset for SWAT Assessments in the US." Water 9, no. 11: 892.
Jungang Gao; Aleksey Y. Sheshukov; Haw Yen; Michael J. White. Impacts of alternative climate information on hydrologic processes with SWAT: A comparison of NCDC, PRISM and NEXRAD datasets. CATENA 2017, 156, 353 -364.
AMA StyleJungang Gao, Aleksey Y. Sheshukov, Haw Yen, Michael J. White. Impacts of alternative climate information on hydrologic processes with SWAT: A comparison of NCDC, PRISM and NEXRAD datasets. CATENA. 2017; 156 ():353-364.
Chicago/Turabian StyleJungang Gao; Aleksey Y. Sheshukov; Haw Yen; Michael J. White. 2017. "Impacts of alternative climate information on hydrologic processes with SWAT: A comparison of NCDC, PRISM and NEXRAD datasets." CATENA 156, no. : 353-364.
Jungang Gao; Aleksey Y. Sheshukov; Haw Yen; Jude H. Kastens; Dana L. Peterson. Impacts of incorporating dominant crop rotation patterns as primary land use change on hydrologic model performance. Agriculture, Ecosystems & Environment 2017, 247, 33 -42.
AMA StyleJungang Gao, Aleksey Y. Sheshukov, Haw Yen, Jude H. Kastens, Dana L. Peterson. Impacts of incorporating dominant crop rotation patterns as primary land use change on hydrologic model performance. Agriculture, Ecosystems & Environment. 2017; 247 ():33-42.
Chicago/Turabian StyleJungang Gao; Aleksey Y. Sheshukov; Haw Yen; Jude H. Kastens; Dana L. Peterson. 2017. "Impacts of incorporating dominant crop rotation patterns as primary land use change on hydrologic model performance." Agriculture, Ecosystems & Environment 247, no. : 33-42.
The proper representation of conservation practices on agricultural lands is an important factor in large-scale assessments of water quality in the United States. Unfortunately, there are few publicly available data sources at the local level and even fewer at the national scale. In this research, randomly selected points within agricultural lands were examined for selected conservation practices using Google Earth aerial imagery by a team of interpreters. In total, 13,530 points had field boundaries digitized, and were subsequently examined and classified. The presence of terraces, grassed waterways, contour farming, center pivot irrigation, strip cropping, ponds, riparian vegetation, filter strips, and land cover were noted. Subjectivity among interpreters was evaluated using duplicate samples and was found to be similar to image misclassification rates in other research. Conservation practice adoption rates for selected major river basins compared favorably with data collected by the Conservation Effects Assessment Project. The frequency of occurrence of each conservation practice was summarized and presented by ecoregion. To facilitate future research, point level data and software source code developed in this research are available via the web at http://nlet.brc.tamus.edu/Conservation. Aerial imagery was found to be a powerful, inexpensive, and easily accessible tool to assess large-scale conservation practice implementation for certain conservation practices.
Michael White; Leighton Haglund; Marcus Gloe; Katrin Bieger; Brandon Namphong; Marilyn Gambone; Eric Hardy; Jungang Gao; Haw Yen; Jeff Arnold. Distribution of Selected Soil and Water Conservation Practices in the U.S. as Identified with Google Earth. JAWRA Journal of the American Water Resources Association 2017, 53, 1229 -1240.
AMA StyleMichael White, Leighton Haglund, Marcus Gloe, Katrin Bieger, Brandon Namphong, Marilyn Gambone, Eric Hardy, Jungang Gao, Haw Yen, Jeff Arnold. Distribution of Selected Soil and Water Conservation Practices in the U.S. as Identified with Google Earth. JAWRA Journal of the American Water Resources Association. 2017; 53 (5):1229-1240.
Chicago/Turabian StyleMichael White; Leighton Haglund; Marcus Gloe; Katrin Bieger; Brandon Namphong; Marilyn Gambone; Eric Hardy; Jungang Gao; Haw Yen; Jeff Arnold. 2017. "Distribution of Selected Soil and Water Conservation Practices in the U.S. as Identified with Google Earth." JAWRA Journal of the American Water Resources Association 53, no. 5: 1229-1240.
Water quality simulation models such as the Soil and Water Assessment Tool (SWAT) and Agricultural Policy EXtender (APEX) are widely used in the US. These models require large amounts of spatial and tabular data to simulate the natural world. Accurate and seamless daily climatic data are critical for accurate depiction of the hydrologic cycle, yet these data are among the most difficult to obtain and process. In this paper we describe the development of a national (US) database of preprocessed climate data derived from monitoring stations applicable to USGS 12-digit watersheds. Various sources and processing methods are explored and discussed. A relatively simple method was employed to choose representative stations for each of the 83,000 12-digit watersheds in the continental US. Fully processed climate data resulting from this research were published online to facilitate other SWAT and APEX modeling efforts in the US.
Michael J. White; Marilyn Gambone; Elizabeth Haney; Jeffrey Arnold; Jungang Gao. Development of a Station Based Climate Database for SWAT and APEX Assessments in the US. Water 2017, 9, 437 .
AMA StyleMichael J. White, Marilyn Gambone, Elizabeth Haney, Jeffrey Arnold, Jungang Gao. Development of a Station Based Climate Database for SWAT and APEX Assessments in the US. Water. 2017; 9 (6):437.
Chicago/Turabian StyleMichael J. White; Marilyn Gambone; Elizabeth Haney; Jeffrey Arnold; Jungang Gao. 2017. "Development of a Station Based Climate Database for SWAT and APEX Assessments in the US." Water 9, no. 6: 437.
The Soil and Water Assessment Tool 2012 (SWAT2012) offers four sediment routing methods as optional alternatives to the default simplified Bagnold method. Previous studies compared only one of these alternative sediment routing methods with the default method. The proposed study evaluated the impacts of all four alternative sediment transport methods on sediment predictions: the modified Bagnold equation, the Kodoatie equation, the Molinas and Wu equation, and the Yang equation. The Arroyo Colorado Watershed, Texas, USA, was first calibrated for daily flow. The sediment parameters were then calibrated to monthly sediment loads, using each of the four sediment routing equations. An automatic calibration tool—Integrated Parameter Estimation and Uncertainty Analysis Tool (IPEAT)—was used to fit model parameters. The four sediment routing equations yielded substantially different sediment sources and sinks. The Yang equation performed best, followed by Kodoatie, Bagnold, and Molinas and Wu equations, according to greater model goodness-of-fit (represented by higher Nash–Sutcliffe Efficiency coefficient and percent bias closer to 0) as well as lower model uncertainty (represented by inclusion of observed data within 95% confidence interval). Since the default method (Bagnold) does not guarantee the best results, modelers should carefully evaluate the selection of alternative methods before conducting relevant studies or engineering projects.
Haw Yen; Shenglan Lu; Qingyu Feng; Ruoyu Wang; Jungang Gao; Dawn Michelle Brady; Amirreza Sharifi; Jungkyu Ahn; Shien-Tsung Chen; Jaehak Jeong; Michael James White; Jeffrey George Arnold. Assessment of Optional Sediment Transport Functions via the Complex Watershed Simulation Model SWAT. Water 2017, 9, 76 .
AMA StyleHaw Yen, Shenglan Lu, Qingyu Feng, Ruoyu Wang, Jungang Gao, Dawn Michelle Brady, Amirreza Sharifi, Jungkyu Ahn, Shien-Tsung Chen, Jaehak Jeong, Michael James White, Jeffrey George Arnold. Assessment of Optional Sediment Transport Functions via the Complex Watershed Simulation Model SWAT. Water. 2017; 9 (2):76.
Chicago/Turabian StyleHaw Yen; Shenglan Lu; Qingyu Feng; Ruoyu Wang; Jungang Gao; Dawn Michelle Brady; Amirreza Sharifi; Jungkyu Ahn; Shien-Tsung Chen; Jaehak Jeong; Michael James White; Jeffrey George Arnold. 2017. "Assessment of Optional Sediment Transport Functions via the Complex Watershed Simulation Model SWAT." Water 9, no. 2: 76.
In recent decades, human activities have significantly transformed land use and land cover (LULC) and the environment of the Central Himalayas region. LULC is a major component of environmental and climatic research. The aim of this study was to determine the changes in cropland status and its drivers in the Koshi River Basin (KRB) of the Central Himalayas region of Nepal between 1978 and 2010. The cropland status in 1978 was obtained from the Land Resources Mapping Project (LRMP) datasets. The cropland status in 1992 and 2010 was determined on the basis of satellite imagery, with an object-oriented classification method, together with field investigations. Advanced geographical tools were used for data processing and binary logistic regression models were used for the statistical analysis of potential driving factors of cropland change. A noticeable overall change in cropland area was found, with rapid increases from 1978 onward at differing rates and to different extents. The cropland area covered 7165 km2 in 1978. It peaked at 7867.49 km2 in 1992, and had reduced slightly (by 90 km2) to 7776.66 km2 by 2010. The change in cropland area was mainly related to four potential driving factors: topography (elevation, slope, and soil types), socioeconomics (population and foreign labor migration), climate (annual mean temperature and precipitation), and neighborhood factors (roads, rivers, and settlements). However, the effects of the different variables have occurred over various stages and at different rates. An understanding of long-term changes in cropland status in the KRB would be useful, and this could be extended to spatial reconstructions with the help of historical data, including cropland and climatic archives.
Basanta Paudel; Jungang Gao; Yili Zhang; Xue Wu; Shicheng Li; Jianzhong Yan. Changes in Cropland Status and Their Driving Factors in the Koshi River Basin of the Central Himalayas, Nepal. Sustainability 2016, 8, 933 .
AMA StyleBasanta Paudel, Jungang Gao, Yili Zhang, Xue Wu, Shicheng Li, Jianzhong Yan. Changes in Cropland Status and Their Driving Factors in the Koshi River Basin of the Central Himalayas, Nepal. Sustainability. 2016; 8 (9):933.
Chicago/Turabian StyleBasanta Paudel; Jungang Gao; Yili Zhang; Xue Wu; Shicheng Li; Jianzhong Yan. 2016. "Changes in Cropland Status and Their Driving Factors in the Koshi River Basin of the Central Himalayas, Nepal." Sustainability 8, no. 9: 933.
Jungang Gao; 吴雪WUXue; 张镱锂ZHANGYili; 刘林山LIULinshan; 王兆锋WANGZhaofeng; 姚治君YAOZhijun. Ecological function regionalization in the lower Jinsha River Basin using analytic hierarchy process method. Acta Ecologica Sinica 2016, 36, 134 -147.
AMA StyleJungang Gao, 吴雪WUXue, 张镱锂ZHANGYili, 刘林山LIULinshan, 王兆锋WANGZhaofeng, 姚治君YAOZhijun. Ecological function regionalization in the lower Jinsha River Basin using analytic hierarchy process method. Acta Ecologica Sinica. 2016; 36 (1):134-147.
Chicago/Turabian StyleJungang Gao; 吴雪WUXue; 张镱锂ZHANGYili; 刘林山LIULinshan; 王兆锋WANGZhaofeng; 姚治君YAOZhijun. 2016. "Ecological function regionalization in the lower Jinsha River Basin using analytic hierarchy process method." Acta Ecologica Sinica 36, no. 1: 134-147.
In this study, we have used four methods to investigate the start of the growing season (SGS) on the Tibetan Plateau (TP) from 1982 to 2012, using Normalized Difference Vegetation Index (NDVI) data obtained from Global Inventory Modeling and Mapping Studies (GIMSS, 1982–2006) and SPOT VEGETATION (SPOT-VGT, 1999–2012). SGS values estimated using the four methods show similar spatial patterns along latitudinal or altitudinal gradients, but with significant variations in the SGS dates. The largest discrepancies are mainly found in the regions with the highest or the lowest vegetation coverage. Between 1982 and 1998, the SGS values derived from the four methods all display an advancing trend, however, according to the more recent SPOT VGT data (1999–2012), there is no continuously advancing trend of SGS on the TP. Analysis of the correlation between the SGS values derived from GIMMS and SPOT between 1999 and 2006 demonstrates consistency in the tendency with regard both to the data sources and to the four analysis methods used. Compared with other methods, the greatest consistency between the in situ data and the SGS values retrieved is obtained with Method 3 (Threshold of NDVI ratio). To avoid error, in a vast region with diverse vegetation types and physical environments, it is critical to know the seasonal change characteristics of the different vegetation types, particularly in areas with sparse grassland or evergreen forest.
Mingjun Ding; Lanhui Li; Yili Zhang; Xiaomin Sun; Linshan Liu; Jungang Gao; Zhaofeng Wang; Yingnian Li. Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data. Journal of Geographical Sciences 2015, 25, 131 -148.
AMA StyleMingjun Ding, Lanhui Li, Yili Zhang, Xiaomin Sun, Linshan Liu, Jungang Gao, Zhaofeng Wang, Yingnian Li. Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data. Journal of Geographical Sciences. 2015; 25 (2):131-148.
Chicago/Turabian StyleMingjun Ding; Lanhui Li; Yili Zhang; Xiaomin Sun; Linshan Liu; Jungang Gao; Zhaofeng Wang; Yingnian Li. 2015. "Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data." Journal of Geographical Sciences 25, no. 2: 131-148.
Jun-Gang Gao; Yi-Li Zhang; Lin-Shan Liu; Zhao-Feng Wang. Climate change as the major driver of alpine grasslands expansion and contraction: A case study in the Mt. Qomolangma (Everest) National Nature Preserve, southern Tibetan Plateau. Quaternary International 2014, 336, 108 -116.
AMA StyleJun-Gang Gao, Yi-Li Zhang, Lin-Shan Liu, Zhao-Feng Wang. Climate change as the major driver of alpine grasslands expansion and contraction: A case study in the Mt. Qomolangma (Everest) National Nature Preserve, southern Tibetan Plateau. Quaternary International. 2014; 336 ():108-116.
Chicago/Turabian StyleJun-Gang Gao; Yi-Li Zhang; Lin-Shan Liu; Zhao-Feng Wang. 2014. "Climate change as the major driver of alpine grasslands expansion and contraction: A case study in the Mt. Qomolangma (Everest) National Nature Preserve, southern Tibetan Plateau." Quaternary International 336, no. : 108-116.
Based on the GIMMS AVHRR NDVI data (8 km spatial resolution) for 1982–2000, the SPOT VEGETATION NDVI data (1 km spatial resolution) for 1998–2009, and observational plant biomass data, the CASA model was used to model changes in alpine grassland net primary production (NPP) on the Tibetan Plateau (TP). This study will help to evaluate the health conditions of the alpine grassland ecosystem, and is of great importance to the promotion of sustainable development of plateau pasture and to the understanding of the function of the national ecological security shelter on the TP. The spatio-temporal characteristics of NPP change were investigated using spatial statistical analysis, separately on the basis of physico-geographical factors (natural zone, altitude, latitude and longitude), river basin, and county-level administrative area. Data processing was carried out using an ENVI 4.8 platform, while an ArcGIS 9.3 and ANUSPLIN platform was used to conduct the spatial analysis and mapping. The primary results are as follows: (1) The NPP of alpine grassland on the TP gradually decreases from the southeast to the northwest, which corresponds to gradients in precipitation and temperature. From 1982 to 2009, the average annual total NPP in the TP alpine grassland was 177.2×1012 gC yr−1(yr represents year), while the average annual NPP was 120.8 gC m−2 yr−1. (2) The annual NPP in alpine grassland on the TP fluctuates from year to year but shows an overall positive trend ranging from 114.7 gC m−2 yr−1 in 1982 to 129.9 gC m−2 yr−1 in 2009, with an overall increase of 13.3%; 32.56% of the total alpine grassland on the TP showed a significant increase in NPP, while only 5.55% showed a significant decrease over this 28-year period. (3) Spatio-temporal characteristics are an important control on annual NPP in alpine grassland: a) NPP increased in most of the natural zones on the TP, only showing a slight decrease in the Ngari montane desert-steppe and desert zone. The positive trend in NPP in the high-cold shrub-meadow zone, high-cold meadow steppe zone and high-cold steppe zone is more significant than that of the high-cold desert zone; b) with increasing altitude, the percentage area with a positive trend in annual NPP follows a trend of “increasing-stable-decreasing”, while the percentage area with a negative trend in annual NPP follows a trend of “decreasing-stable-increasing”, with increasing altitude; c) the variation in annual NPP with latitude and longitude co-varies with the vegetation distribution; d) the variation in annual NPP within the major river basins has a generally positive trend, of which the growth in NPP in the Yellow River Basin is most significant. Results show that, based on changes in NPP trends, vegetation coverage and phonological phenomenon with time, NPP has been declining in certain places successively, while the overall health of the alpine grassland on the TP is improving.
Yili Zhang; Wei Qi; Caiping Zhou; Mingjun Ding; Linshan Liu; Jungang Gao; Wanqi Bai; Zhaofeng Wang; Du Zheng. Spatial and temporal variability in the net primary production of alpine grassland on the Tibetan Plateau since 1982. Journal of Geographical Sciences 2014, 24, 269 -287.
AMA StyleYili Zhang, Wei Qi, Caiping Zhou, Mingjun Ding, Linshan Liu, Jungang Gao, Wanqi Bai, Zhaofeng Wang, Du Zheng. Spatial and temporal variability in the net primary production of alpine grassland on the Tibetan Plateau since 1982. Journal of Geographical Sciences. 2014; 24 (2):269-287.
Chicago/Turabian StyleYili Zhang; Wei Qi; Caiping Zhou; Mingjun Ding; Linshan Liu; Jungang Gao; Wanqi Bai; Zhaofeng Wang; Du Zheng. 2014. "Spatial and temporal variability in the net primary production of alpine grassland on the Tibetan Plateau since 1982." Journal of Geographical Sciences 24, no. 2: 269-287.
Yili Zhang; Jungang Gao; Linshan Liu; Zhaofeng Wang; Minjung Ding; Xuchao Yang. NDVI-based vegetation changes and their responses to climate change from 1982 to 2011: A case study in the Koshi River Basin in the middle Himalayas. Global and Planetary Change 2013, 108, 139 -148.
AMA StyleYili Zhang, Jungang Gao, Linshan Liu, Zhaofeng Wang, Minjung Ding, Xuchao Yang. NDVI-based vegetation changes and their responses to climate change from 1982 to 2011: A case study in the Koshi River Basin in the middle Himalayas. Global and Planetary Change. 2013; 108 ():139-148.
Chicago/Turabian StyleYili Zhang; Jungang Gao; Linshan Liu; Zhaofeng Wang; Minjung Ding; Xuchao Yang. 2013. "NDVI-based vegetation changes and their responses to climate change from 1982 to 2011: A case study in the Koshi River Basin in the middle Himalayas." Global and Planetary Change 108, no. : 139-148.
Based on monthly mean, maximum, and minimum air temperature and monthly mean precipitation data from 10 meteorological stations on the southern slope of the Mt. Qomolangma region in Nepal between 1971 and 2009, the spatial and temporal characteristics of climatic change in this region were analyzed using climatic linear trend, Sen’s Slope Estimates and Mann-Kendall Test analysis methods. This paper focuses only on the southern slope and attempts to compare the results with those from the northern slope to clarify the characteristics and trends of climatic change in the Mt. Qomolangma region. The results showed that: (1) between 1971 and 2009, the annual mean temperature in the study area was 20.0°C, the rising rate of annual mean temperature was 0.25°C/10a, and the temperature increases were highly influenced by the maximum temperature in this region. On the other hand, the temperature increases on the northern slope of Mt. Qomolangma region were highly influenced by the minimum temperature. In 1974 and 1992, the temperature rose noticeably in February and September in the southern region when the increment passed 0.9°C. (2) Precipitation had an asymmetric distribution; between 1971 and 2009, the annual precipitation was 1729.01 mm. In this region, precipitation showed an increasing trend of 4.27 mm/a, but this was not statistically significant. In addition, the increase in rainfall was mainly concentrated in the period from April to October, including the entire monsoon period (from June to September) when precipitation accounts for about 78.9% of the annual total. (3) The influence of altitude on climate warming was not clear in the southern region, whereas the trend of climate warming was obvious on the northern slope of Mt. Qomolangma. The annual mean precipitation in the southern region was much higher than that of the northern slope of the Mt. Qomolangma region. This shows the barrier effect of the Himalayas as a whole and Mt. Qomolangma in particular.
Wei Qi; Yili Zhang; Jungang Gao; Xuchao Yang; Linshan Liu; Narendra Khanal. Climate change on the southern slope of Mt. Qomolangma (Everest) Region in Nepal since 1971. Journal of Geographical Sciences 2013, 23, 595 -611.
AMA StyleWei Qi, Yili Zhang, Jungang Gao, Xuchao Yang, Linshan Liu, Narendra Khanal. Climate change on the southern slope of Mt. Qomolangma (Everest) Region in Nepal since 1971. Journal of Geographical Sciences. 2013; 23 (4):595-611.
Chicago/Turabian StyleWei Qi; Yili Zhang; Jungang Gao; Xuchao Yang; Linshan Liu; Narendra Khanal. 2013. "Climate change on the southern slope of Mt. Qomolangma (Everest) Region in Nepal since 1971." Journal of Geographical Sciences 23, no. 4: 595-611.
Only few models for land-cover classification incorporated spectral data into ordinary logistic regression (OL model) in the Mt. Qomolangma (Everest) National Nature Preserve (QNNP) in China. In this study, spectral variables were incorporated into OL model and autologistic regression (AL) model to classify six main land covers. Twelve environmental variables and seven spectral variables of 10,000 stratified random sites in the QNNP were quantified and analyzed; OL model, AL model, OL model with spectral data (OLM model), and AL model with spectral data (ALM model) were estimated. The OLM and ALM models produced better estimates of regression coefficients and significantly improved model performance and overall accuracy for the grassland, sparsely vegetated land, and bare land compared with OL and AL models.
Jungang Gao; Yili Zhang. Incorporating spectral data into logistic regression model to classify land cover: a case study in Mt. Qomolangma (Everest) National Nature Preserve. International Journal of Geographical Information Science 2012, 26, 1845 -1862.
AMA StyleJungang Gao, Yili Zhang. Incorporating spectral data into logistic regression model to classify land cover: a case study in Mt. Qomolangma (Everest) National Nature Preserve. International Journal of Geographical Information Science. 2012; 26 (10):1845-1862.
Chicago/Turabian StyleJungang Gao; Yili Zhang. 2012. "Incorporating spectral data into logistic regression model to classify land cover: a case study in Mt. Qomolangma (Everest) National Nature Preserve." International Journal of Geographical Information Science 26, no. 10: 1845-1862.
The spatial functions of surface area density (vegetative surface area per unit canopy volume) and cubic density (vegetative volume per unit canopy volume) have been used as two three-dimensional (3D) structural descriptors for shelterbelt. The functions were defined by models as a general case. However, sub-models such as surface area, volume, and corresponding distributions were not explicitly defined for poplar trees, which are a dominant woody species in shelterbelts all over China, and this limits applications of the models in China and elsewhere. In order to define and develop these sub-models for shelterbelts, poplar trees were destructively sampled from multiple-row shelterbelts and then were measured for their surface area and volume. Using these measurements, we estimated parameters to define their equations explicitly. Based on the architecture and planting patterns of trees in shelterbelts, the distribution of the surface areas and volumes vertically and across the width for different tree heights were constructed for the three components of trunks, branches and leaves. Incorporating the defined equations into the models, we described the 3D structure of a multiple-row poplar shelterbelt. The results showed that, the spatial change in magnitude of surface area density (0.215–10.131 m2/m3) or cubic density (0.00007–0.04667 m3/m3) in shelterbelts is large and their distributions are not uniform. The assumption for boundary-layer flow modeling efforts that the 3D distribution of shelterbelt structure was uniform is not the case in field. The 3D structure model not only can be used to model the flow field as influenced by each tree component, but also can express the entire aerodynamic characteristics of a shelterbelt. The methodologies and equations that are developed in this study can be applied to estimate the 3D structure of a shelterbelt with a design similar to our studied poplar shelterbelts in terms of species composition and planting patterns. The fitted models can be used to describe the 3D aerodynamic structure of field shelterbelts. Furthermore, an improved description of shelterbelt structure has great potential to improve the simulation of boundary layer flows as influenced by that shelterbelt. Such insights can eventually be used to quantify the design of shelterbelt structure and/or adjustment for managing the function of shelterbelts and their effects on microclimate.
Zhiping Fan; Jungang Gao; Dehui Zeng; Xinhua Zhou; Xuekai Sun. Three-dimensional (3D) structure model and its parameters for poplar shelterbelts. Science China Earth Sciences 2010, 53, 1513 -1526.
AMA StyleZhiping Fan, Jungang Gao, Dehui Zeng, Xinhua Zhou, Xuekai Sun. Three-dimensional (3D) structure model and its parameters for poplar shelterbelts. Science China Earth Sciences. 2010; 53 (10):1513-1526.
Chicago/Turabian StyleZhiping Fan; Jungang Gao; Dehui Zeng; Xinhua Zhou; Xuekai Sun. 2010. "Three-dimensional (3D) structure model and its parameters for poplar shelterbelts." Science China Earth Sciences 53, no. 10: 1513-1526.