Zhuotong Nan

A Decision Support System for irrigation water allocation along the middle reaches of the Heihe River Basin, Northwest China

To improve the water resource management of the inland river basins of northwestern China, a Decision Support System (DSS) is developed to provide an operative computer platform for decision makers. The DSS is designed according to actual water resource management problems and is seamlessly integrated into a user-friendly interface implemented in the Visual C# programming language. The DSS comprises an information management system that performs data collection, verification, management, and visualization, and models estimated crop water demand and water allocation for different levels of water use units. The objective of this study is to aid in the decision-making process related to water allocation scheme planning and implementation and to aid real-time responses to changes in water supply, allowing a new water allocation scheme to be developed based on the actual relationship between the supply and demand for water. The system is tested to allocate water to different levels of water use units as a standard decision support tool by means of the actual total available water from rivers, reservoirs, and groundwater. More than 60 water decision makers use the system at more than 40 locations along the middle reaches of the Heihe River Basin. A water resource management Decision Support System (HD) was developed.We developed some multi-level water resources management models.The impact factors of water resources management were analyzed.Irrigation water allocation schemes can be quickly scheduled using HD.

GRACE Gravity Satellite Observations of Terrestrial Water Storage Changes for Drought Characterization in the Arid Land of Northwestern China

Drought is a complex natural hazard which can have negative effects on agriculture, economy, and human life. In this paper, the primary goal is to explore the application of the Gravity Recovery and Climate Experiment (GRACE) gravity satellite data for the quantitative investigation of the recent drought dynamic over the arid land of northwestern China, a region with scarce hydrological and meteorological observation datasets. The spatiotemporal characteristics of terrestrial water storage changes (TWSC) were first evaluated based on the GRACE satellite data, and then validated against hydrological model simulations and precipitation data. A drought index, the total storage deficit index (TSDI), was derived on the basis of GRACE-recovered TWSC. The spatiotemporal distributions of drought events from 2003 to 2012 in the study region were obtained using the GRACE-derived TSDI. Results derived from TSDI time series indicated that, apart from four short-term (three months) drought events, the study region experienced a severe long-term drought from May 2008 to December 2009. As shown in the spatial distribution of TSDI-derived drought conditions, this long-term drought mainly concentrated in the northwestern area of the entire region, where the terrestrial water storage was in heavy deficit. These drought characteristics, which were detected by TSDI, were consistent with local news reports and other researchers’ results. Furthermore, a comparison between TSDI and Standardized Precipitation Index (SPI) implied that GRACE TSDI was a more reliable integrated drought indicator (monitoring agricultural and hydrological drought) in terms of considering total terrestrial water storages for large regions. The GRACE-derived TSDI can therefore be used to characterize and monitor large-scale droughts in the arid regions, being of special value for areas with scarce observations.

Modeling Land-Use and Land-Cover Change and Hydrological Responses under Consistent Climate Change Scenarios in the Heihe River Basin, China

This study investigated land-use and land-cover change (LUCC) and hydrological responses under consistent climate change scenarios (A1B and B1) in the Heihe River Basin (HRB), a typical arid inland river basin in northwest China. LUCC was first projected using the Dynamic Conversion of Land-Use and its Effects (Dyna-CLUE) model. Two cases (Case 1 and Case 2) were then established to quantify the hydrological responses to single climate change and the combined responses to climate change and LUCC with the Soil and Water Assessment Tool (SWAT). The results of LUCC modeling under the A1B and B1 scenarios present distinct regional characteristics and also indicate that the projected future land-use patterns are not appreciably different than the actual map for the year 2000. In Case 1, which only considers the impacts of single climate change, overall, the streamflow at the outlet of the upper HRB is projected to decline, whereas at the outlet of the middle HRB to increase, under both climate change scenarios. Meanwhile, the frequency of occurrence of hydrological extremes is expect to increase under both scenarios. In Case 2, which considers the combined impacts of climate change and LUCC, the changes in streamflow and frequency of hydrological extremes are found to be remarkably consistent with those in Case 1. The results imply that climate change rather than LUCC are primarily responsible for the hydrological variations. The role of LUCC varies with regions in the context of climate change dominated hydrological responses.

Toward an improved data stewardship and service for environmental and ecological science data in West China

Abstract Sharing of scientific data can help scientific research to flourish and facilitate more widespread use of scientific data for the benefit of society. The Environmental and Ecological Science Data Center for West China (WestDC), sponsored by the National Natural Science Foundation of China (NSFC), aims to collect, manage, integrate, and disseminate environmental and ecological data from western China. It also aims to provide a long-term data service for multidisciplinary research within NSFCs “Environment and Ecology of West China Research Plan” (NSFC West Plan). An integrated platform has been developed by the WestDC, and this has the function of data sharing, acting as a knowledge repository. Major data sets developed by the WestDC include basic geographic data, the regionalization of global data set for China, scientific data for cold and arid regions in China, scientific data for the cryosphere in countries that neighbor China, data relating to the inland river basins in northwestern China, and data submitted by the NSFC West Plan projects. In compliance with the “full and open” data sharing policy, most data in the WestDC can be accessed online. Highlights include detailed data documentation, the integration of data with bibliographic knowledge, data publishing, and data reference.

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China.

Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995–2014) and near future (2015–2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses.

Analysis of Spatial Similarities Between NEXRAD and NLDAS Precipitation Data Products

Precipitation is one of the key inputs for hydrological modeling. Although the Multisensor Precipitation Estimator (MPE) from NEXRAD (Next Generation Radar) and the NLDAS (North American Land Data Assimilation System) precipitation data have been extensively used in various hydrological and climatic studies, there has been no systematic investigation of the spatial similarities and differences between them, based on long-term time series data over a large spatial region. In this study, six years of hourly and daily precipitation time series data from NEXRAD and NLDAS were investigated for their spatial similarities, over a subregion of the Ohio River basin. Three spatial metrics were used: Cohens Kappa coefficient, Forecast Quality Index (FQI), and displacement-based Forecast Quality Measure (FQM). The three metrics were also applied to the two data products after stratification by season (warm, cold). Results show that significant differences exist between NEXRAD MPE and NLDAS. Analyses and discussions are presented on possible causes of the dissimilarities. In addition, results show that a single metric cannot adequately represent their spatial characteristics. The three metrics are complementary to each other and, when used jointly, can provide a more complete picture of the similarities and differences between the two precipitation products. However, if a single metric is desired, then a more comprehensive one needs to be developed to effectively account for magnitude, distance, shape, and neighborhood effects.

An Effective Interpolation Method for MODIS Land Surface Temperature on the Qinghai–Tibet Plateau

Land surface temperature (LST) is a key parameter in the processes of energy and water exchange between land and atmosphere. However, the MODIS LST products are often obscured by clouds and other atmospheric disturbances, resulting in severe data loss. Traditional interpolation methods cannot be effectively applied when there is large area of missing data. Thus, in this study, an effective LST interpolation method is developed to address this issue and is used to interpolate MODIS/Terra LST data on the Qinghai-Tibet Plateau in 2005. This method assumes that some pixels with spatially valid LSTs may follow a change trend over time similar to the null pixels, and the focus thus becomes to locate those similar pixels to interpolate each null pixel. First, LST images with a small amount of missing data, chosen as the reference images, were interpolated using a traditional interpolation method. Then, for each null pixel, other pixels with similar temporal changes of LST were identified by a similarity function. Finally, a transfer function for each null pixel was established based on those pixels most similar to it in the interpolated image and the corresponding reference image. The results were found to be much superior to those interpolated by traditional methods, such as regression Kriging, ordinary Kriging, and IDW. A specially designed experiment on an area that had ample valid LSTs confirmed that the proposed method can produce more favorable results than the other methods, and performed especially well when there was a significant lack of data.

Estimating groundwater storage changes in the Heihe river basin using grace

As a typical inland river basin in the arid region of northwestern China, the Heihe river basin (HRB) can only provide limited available surface water resources, resulting in overexploitation of groundwater resources. In this paper, temporal and spatial variations of groundwater in HRB are derived from GRACE. This approach is successfully employed in HRB thus offering new insight into monitoring groundwater variations in a river basin with limited or even without any observed data. Our analysis indicates that groundwater storage in HRB reaches its highest peak in 2005 summer, and then begins shrink and no increase in 2008. Spatially, groundwater shows decline in upper HRB in first two years and slightly increase in following years, which is opposite to that in middle HRB where groundwater slightly increases in 2005 and then declines in following three years. In lower HRB, GRACE detects a continual increase in the total 6 study years.

Vegetation Changes in the Permafrost Regions of the Qinghai-Tibetan Plateau from 1982-2012: Different Responses Related to Geographical Locations and Vegetation Types in High-Altitude Areas

The Qinghai-Tibetan Plateau (QTP) contains the largest permafrost area in a high-altitude region in the world, and the unique hydrothermal environments of the active layers in this region have an important impact on vegetation growth. Geographical locations present different climatic conditions, and in combination with the permafrost environments, these conditions comprehensively affect the local vegetation activity. Therefore, the responses of vegetation to climate change in the permafrost region of the QTP may be varied differently by geographical location and vegetation condition. In this study, using the latest Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) product based on turning points (TPs), which were calculated using a piecewise linear model, 9 areas within the permafrost region of the QTP were selected to investigate the effect of geographical location and vegetation type on vegetation growth from 1982 to 2012. The following 4 vegetation types were observed in the 9 selected study areas: alpine swamp meadow, alpine meadow, alpine steppe and alpine desert. The research results show that, in these study areas, TPs mainly appeared in 2000 and 2001, and almost 55.1% and 35.0% of the TPs were located in 2000 and 2001. The global standardized precipitation evapotranspiration index (SPEI) and 7 meteorological variables were selected to analyze their correlations with NDVI. We found that the main correlative variables to vegetation productivity in study areas from 1982 to 2012 were precipitation, surface downward long-wave radiation and temperature. Furthermore, NDVI changes exhibited by different vegetation types within the same study area followed similar trends. The results show that regional effects rather than vegetation type had a larger impact on changes in vegetation growth in the permafrost regions of the QTP, indicating that climatic factors had a larger impact in the permafrost regions than the environmental factors (including permafrost) related to the underlying surface conditions.

Distribution of Soils and Landform Relationships in Permafrost Regions of the Western Qinghai-Xizang (Tibetan) Plateau, China

Abstract We evaluated software predictions involving soil distributions across landscape positions using selected soil morphology and terrain features in the permafrost regions of the Qinghai-Xizang (Tibetan) Plateau. The relationships presented are based on the Soil Taxonomy System and the 2010 soil suborders coupled with defined environmental factors and predict the spatial distribution of the soil suborders, using the See 5.0 decision tree software integrated with the soil-land inference model. Ten environmental factors closely related to permafrost-affected soil formation were selected as variables for the model: soil parent material, land surface temperatures, elevation, slope gradient, slope aspect, planform and profile curvatures, wetness index, and Normalized Difference Vegetation Index. A total of 62 soil profiles from 2010 were used for model building and validation. The results showed that the soils in the study area were primarily Turbels, Cryids, and Psamments, which cover 47.9%, 22.3%, and 11.7%, respectively, of the total area. Altitude had the closest relationship with soil type; in addition, permafrost played an important role in the soil-forming processes, which led to higher water content in the higher altitudes than in the lower altitudes in the arid areas. The thickness of the active layer in the study area was usually more than 2 m; however, additional consideration of the thickness of the active layer within the Soil Taxonomy System is required.