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Min Luo
College of Geographical Science, Inner Mongolia Normal University, Hohhot, China

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Article
Published: 23 March 2021 in Journal of Arid Land
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Snow cover is an important water source for vegetation growth in arid and semi-arid areas, and grassland phenology provides valuable information on the response of terrestrial ecosystems to climate change. The Mongolian Plateau features both abundant snow cover resources and typical grassland ecosystems. In recent years, with the intensification of global climate change, the snow cover on the Mongolian Plateau has changed correspondingly, with resulting effects on vegetation growth. In this study, using MOD10A1 snow cover data and MOD13A1 Normalized Difference Vegetation Index (NDVI) data combined with remote sensing (RS) and geographic information system (GIS) techniques, we analyzed the spatiotemporal changes in snow cover and grassland phenology on the Mongolian Plateau from 2001 to 2018. The correlation analysis and grey relation analysis were used to determine the influence of snow cover parameters (snow cover fraction (SCF), snow cover duration (SCD), snow cover onset date (SCOD), and snow cover end date (SCED)) on different types of grassland vegetation. The results showed wide snow cover areas, an early start time, a late end time, and a long duration of snow cover over the northern Mongolian Plateau. Additionally, a late start, an early end, and a short duration were observed for grassland phenology, but the southern area showed the opposite trend. The SCF decreased at an annual rate of 0.33%. The SCD was shortened at an annual rate of 0.57 d. The SCOD and SCED in more than half of the study area advanced at annual rates of 5.33 and 5.74 DOY (day of year), respectively. For grassland phenology, the start of the growing season (SOS) advanced at an annual rate of 0.03 DOY, the end of the growing season (EOS) was delayed at an annual rate of 0.14 DOY, and the length of the growing season (LOS) was prolonged at an annual rate of 0.17 d. The SCF, SCD, and SCED in the snow season were significantly positively correlated with the SOS and negatively correlated with the EOS and LOS. The SCOD was significantly negatively correlated with the SOS and positively correlated with the EOS and LOS. The SCD and SCF can directly affect the SOS of grassland vegetation, while the EOS and LOS were obviously influenced by the SCOD and SCED. This study provides a scientific basis for exploring the response trends of alpine vegetation to global climate change.

ACS Style

Chula Sa; Fanhao Meng; Min Luo; Chenhao Li; Mulan Wang; Saruulzaya Adiya; Yuhai Bao. Spatiotemporal variation in snow cover and its effects on grassland phenology on the Mongolian Plateau. Journal of Arid Land 2021, 13, 332 -349.

AMA Style

Chula Sa, Fanhao Meng, Min Luo, Chenhao Li, Mulan Wang, Saruulzaya Adiya, Yuhai Bao. Spatiotemporal variation in snow cover and its effects on grassland phenology on the Mongolian Plateau. Journal of Arid Land. 2021; 13 (4):332-349.

Chicago/Turabian Style

Chula Sa; Fanhao Meng; Min Luo; Chenhao Li; Mulan Wang; Saruulzaya Adiya; Yuhai Bao. 2021. "Spatiotemporal variation in snow cover and its effects on grassland phenology on the Mongolian Plateau." Journal of Arid Land 13, no. 4: 332-349.

Journal article
Published: 23 January 2021 in Sustainability
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Rivers located in high altitude mountainous areas provide a large number of water resources and are also high-risk areas for seasonal snow melt floods. The accurate calculation and simulation of snow melting processes can provide reliable data for flood disaster prediction. In order to make the Soil and Water Assessment Tool (SWAT) model more suitable for high altitude mountainous areas, the effect of the daily accumulated temperature on the precipitation pattern and snow melting is fully considered. Applying the modified model to three mountain systems with different latitudes in Xinjiang can not only improve our understanding of the characteristics of snowmelt flooding but can also be used to test the applicability of the modified model. Through comparison, it was found that the simulation accuracy of the modified model of the flood peak value was improved by 56.19%. The correlation coefficient between the Normalized Difference Vegetation Index (NDVI) and snowmelt increased from 0.27 to 0.68. This study provides a new method for accurately understanding the process of snowmelt runoff in the mountainous area and provides new insights into the effects of snowmelt runoff on vegetation growth at different latitudes.

ACS Style

Yongchao Duan; Min Luo; Xiufeng Guo; Peng Cai; Fu Li. Study on the Relationship between Snowmelt Runoff for Different Latitudes and Vegetation Growth Based on an Improved SWAT Model in Xinjiang, China. Sustainability 2021, 13, 1189 .

AMA Style

Yongchao Duan, Min Luo, Xiufeng Guo, Peng Cai, Fu Li. Study on the Relationship between Snowmelt Runoff for Different Latitudes and Vegetation Growth Based on an Improved SWAT Model in Xinjiang, China. Sustainability. 2021; 13 (3):1189.

Chicago/Turabian Style

Yongchao Duan; Min Luo; Xiufeng Guo; Peng Cai; Fu Li. 2021. "Study on the Relationship between Snowmelt Runoff for Different Latitudes and Vegetation Growth Based on an Improved SWAT Model in Xinjiang, China." Sustainability 13, no. 3: 1189.

Journal article
Published: 27 April 2020 in Sustainability
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The sustainability of water resources in mountainous areas has a significant contribution to the stabilization and persistence of the ecological and agriculture systems in arid and semi-arid areas. However, the insufficient understanding of hydrological processes in ungauged mountainous catchments (UMCs) is not able to scientifically support the sustainable management of water resources. The conventional parameter transferability method (transplanting the parameters of the donor catchment model with similar distances or attributes to the target catchment model) still has great potential for improving the accuracy of the hydrological simulation in UMC. In this study, 46 river catchments, with discharge survey stations and multi-type catchment characteristics in Xinjiang, are separated into the target catchments and donor catchments to promote an improved model parameter transferability method (IMPTM). This method synthetically processes the SWAT model parameters based on the distance approximation principle (DAP) and the attribute similarity principle (ASP). The performance of this method is tested in a random gauged catchment and compared with other traditional methods (DAP and ASP). The daily runoff simulation results in the target catchment have relatively low accuracy by both the DAP method ( N S = 0.27, R 2 = 0.55) and ASP method ( N S = 0.36, R 2 = 0.65), which implies the conventional approach is not capable of processing the parameters in the target regions. However, the simulation result by IMPTM is a significant improvement ( N S = 0.69, R 2 = 0.85). Moreover, the IMPTM can accurately catch the flow peak, appearance time, and recession curve. The current study provides a compatible method to overcome the difficulties of hydrological simulation in UMCs in the world and can benefit hydrological forecasting and water resource estimation in mountainous areas.

ACS Style

Fanhao Meng; Chula Sa; Tie Liu; Min Luo; Jiao Liu; Lin Tian. Improved Model Parameter Transferability Method for Hydrological Simulation with SWAT in Ungauged Mountainous Catchments. Sustainability 2020, 12, 3551 .

AMA Style

Fanhao Meng, Chula Sa, Tie Liu, Min Luo, Jiao Liu, Lin Tian. Improved Model Parameter Transferability Method for Hydrological Simulation with SWAT in Ungauged Mountainous Catchments. Sustainability. 2020; 12 (9):3551.

Chicago/Turabian Style

Fanhao Meng; Chula Sa; Tie Liu; Min Luo; Jiao Liu; Lin Tian. 2020. "Improved Model Parameter Transferability Method for Hydrological Simulation with SWAT in Ungauged Mountainous Catchments." Sustainability 12, no. 9: 3551.

Journal article
Published: 03 January 2020 in Remote Sensing
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While mountain runoff provides great potential for the development and life quality of downstream populations, it also frequently causes seasonal disasters. The accurate modeling of hydrological processes in mountainous areas, as well as the amount of meltwater from ice and snow, is of great significance for the local sustainable development, hydropower regulations, and disaster prevention. In this study, an improved model, the Soil Water Assessment Tool with added ice-melt module (SWATAI) was developed based on the Soil Water Assessment Tool (SWAT), a semi-distributed hydrological model, to simulate ice and snow runoff. A temperature condition used to determine precipitation types has been added in the SWATAI model, along with an elevation threshold and an accumulative daily temperature threshold for ice melt, making it more consistent with the runoff process of ice and snow. As a supplementary reference, the comparison between the normalized difference vegetation index (NDVI) and the quantity of meltwater were conducted to verify the simulation results and assess the impact of meltwater on the ecology. Through these modifications, the accuracy of the daily flow simulation results has been considerably improved, and the contribution rate of ice and snow melt to the river discharge calculated by the model increased by 18.73%. The simulation comparison of the flooding process revealed that the accuracy of the simulated peak flood value by the SWATAI was 77.65% higher than that of the SWAT, and the temporal accuracy was 82.93% higher. The correlation between the meltwater calculated by the SWATAI and the NDVI has also improved significantly. This improved model could simulate the flooding processes with high temporal resolution in alpine regions. The simulation results could provide technical support for economic benefits and reasonable reference for flood prevention.

ACS Style

Yongchao Duan; Tie Liu; Fanhao Meng; Ye Yuan; Min Luo; Yue Huang; Wei Xing; Vincent Nzabarinda; Philippe De Maeyer. Accurate Simulation of Ice and Snow Runoff for the Mountainous Terrain of the Kunlun Mountains, China. Remote Sensing 2020, 12, 179 .

AMA Style

Yongchao Duan, Tie Liu, Fanhao Meng, Ye Yuan, Min Luo, Yue Huang, Wei Xing, Vincent Nzabarinda, Philippe De Maeyer. Accurate Simulation of Ice and Snow Runoff for the Mountainous Terrain of the Kunlun Mountains, China. Remote Sensing. 2020; 12 (1):179.

Chicago/Turabian Style

Yongchao Duan; Tie Liu; Fanhao Meng; Ye Yuan; Min Luo; Yue Huang; Wei Xing; Vincent Nzabarinda; Philippe De Maeyer. 2020. "Accurate Simulation of Ice and Snow Runoff for the Mountainous Terrain of the Kunlun Mountains, China." Remote Sensing 12, no. 1: 179.