Characteristics of integrated droughts based on a nonparametric standardized drought index in the Yellow River Basin, China

2015 ◽  
Vol 47 (2) ◽  
pp. 454-467 ◽  
Author(s):  
Yuelu Zhu ◽  
Jianxia Chang ◽  
Shengzhi Huang ◽  
Qiang Huang
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Yellow River ◽  
Standardized Precipitation Index ◽  
Yellow River Basin ◽  
Drought Indices ◽  
The Yellow River ◽  
The Yellow River Basin ◽  
Multivariate Drought Index ◽  
Annual Time

Most current drought indices rely on a representative parametric distribution function to fit data, which results in different tail behaviors. Additionally, a drought index based on a single variable may not be sufficient for monitoring drought conditions timely and reliably. Therefore, a nonparametric multivariate drought index (NMSDI) combined with the information of precipitation and streamflow was introduced in this study, without assuming representative parametric distributions. It was applied to characterize drought in the Yellow River Basin (YRB) on seasonal and annual scales. Results indicate that: (1) the variations of developed NMSDI is well consistent with those of 1-month SPI (standardized precipitation index) and SSI (standardized streamflow index), indicating the reliability and effectiveness of the newly proposed nonparametric based drought index; (2) a decreasing NMSDI trend was found over the period of 1952–2012 at seasonal and annual time scales, which would reverse in the future as suggested by the Hurst index; (3) no significant change points were detected for the annual NMSDI series over the YRB except one (i.e. the year 1991) in the middle streamflow sub-basin Wei River Basin (WRB) which was primarily caused by the combined effects of climate change and human activities.

scholarly journals Drought Monitoring over Yellow River Basin from 2003–2019 Using Reconstructed MODIS Land Surface Temperature in Google Earth Engine

2021 ◽  
Vol 13 (18) ◽  
pp. 3748
Author(s):  
Xiaoyang Zhao ◽  
Haoming Xia ◽  
Li Pan ◽  
Hongquan Song ◽  
Wenhui Niu ◽  
...  
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Drought Index ◽  
Yellow River ◽  
Yellow River Basin ◽  
Condition Index ◽  
Drought Indices ◽  
The Yellow River ◽  
Drought Conditions ◽  
The Yellow River Basin

Drought is one of the most complex and least-understood environmental disasters that can trigger environmental, societal, and economic problems. To accurately assess the drought conditions in the Yellow River Basin, this study reconstructed the Land Surface Temperature (LST) using the Annual Temperature Cycle (ATC) model and the Normalized Difference Vegetation Index (NDVI). The Temperature Condition Index (TCI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Temperature-Vegetation Drought Index (TVDI), which are four typical remote sensing drought indices, were calculated. Then, the air temperature, precipitation, and soil moisture data were used to evaluate the applicability of each drought index to different land types. Finally, this study characterized the spatial and temporal patterns of drought in the Yellow River Basin from 2003 to 2019. The results show that: (1) Using the LST reconstructed by the ATC model to calculate the drought index can effectively improve the accuracy of drought monitoring. In most areas, the reconstructed TCI, VHI, and TVDI are more reliable for monitoring drought conditions than the unreconstructed VCI. (2) The four drought indices (TCI, VCI, VH, TVDI) represent the same temporal and spatial patterns throughout the study area. However, in some small areas, the temporal and spatial patterns represented by different drought indices are different. (3) In the Yellow River Basin, the drought level is highest in the northwest and lowest in the southwest and southeast. The dry conditions in the Yellow River Basin were stable from 2003 to 2019. The results in this paper provide a basis for better understanding and evaluating the drought conditions in the Yellow River Basin and can guide water resources management, agricultural production, and ecological protection of this area.

scholarly journals Capability of Remotely Sensed Drought Indices for Representing the Spatio–Temporal Variations of the Meteorological Droughts in the Yellow River Basin

2018 ◽  
Author(s):  
Fei Wang ◽  
Zongmin Wang ◽  
Haibo Yang ◽  
Yong Zhao ◽  
Zhenhong Li ◽  
...  
Keyword(s):  
Drought Index ◽  
Yellow River ◽  
Yellow River Basin ◽  
Condition Index ◽  
Remotely Sensed ◽  
Temporal Variations ◽  
Drought Indices ◽  
The Yellow River ◽  
The Yellow River Basin ◽  
Meteorological Droughts

Due to the advantages of wide coverage and continuity, remotely sensed data are widely used for large-scale drought monitoring to compensate the deficiency and discontinuity of meteorological data. However, few researches have focused on the capability of various remotely sensed drought indices (RSDIs) for representing the spatio-temporal variations of the meteorological droughts. In this study, five RSDIs, namely Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Modified Temperature Vegetation Dryness Index (MTVDI) and Normalized Vegetation Supply Water Index (NVSWI) were calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) monthly NDVI and LST. The monthly NDVI and LST data were filtered by Savitzky-Golay (S-G) filtering method. Meteorological station-based drought index represented by Standardized Precipitation Evapotranspiration Index (SPEI) was compared with RSDIs. And the dimensionless Skill Score (SS) method was adopted to identify the spatiotemporally optimal RSDIs for presenting the meteorological droughts in the Yellow River basin (YRB) from 2000 to 2015. The results indicated that (1) RSDIs revealed a decreasing trend to the overall YRB consistent with SPEI except for in winter, and different variations of seasonal trends spatially; (2) the optimal RSDIs in spring, summer, autumn and winter were VHI, TCI, MTVDI and VCI, respectively, and the average correlation coefficient between the RSDIs and SPEI was 0.577 (=0.05); (3) different RSDIs have a 0–3 months’ time-lags compared with meteorological drought index.

Drought structure based on a nonparametric multivariate standardized drought index across the Yellow River basin, China

2015 ◽  
Vol 530 ◽  
pp. 127-136 ◽  
Author(s):  
Shengzhi Huang ◽  
Qiang Huang ◽  
Jianxia Chang ◽  
Yuelu Zhu ◽  
Guoyong Leng ◽  
...  
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
The Yellow River Basin ◽  
Standardized Drought Index

scholarly journals Nitrogen Fertilization Effects on Physiology of the Cotton Boll–Leaf System

Agronomy ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 271
Author(s):  
Jing Chen ◽  
Liantao Liu ◽  
Zhanbiao Wang ◽  
Hongchun Sun ◽  
Yongjiang Zhang ◽  
...  
Keyword(s):  
River Basin ◽  
Nitrogen Fertilization ◽  
Yellow River ◽  
Yellow River Basin ◽  
Growth And Yield ◽  
The Yellow River ◽  
Nitrogen Rate ◽  
The Yellow River Basin ◽  
Source Sink ◽  
Subtending Leaves

The objective of this study was to assess the impacts of nitrogen on the physiological characteristics of the source–sink system of upper fruiting branches under various amounts of nitrogen fertilization. A two-year field experiment was conducted with a Bt cotton cultivar in the Yellow River Basin of China. The growth and yield of cotton of the upper fruiting branches were compared under four nitrogen levels: Control (N0, 0 kg ha−1), low nitrogen (N1, 120 kg ha−1), moderate nitrogen (N2, 240 kg ha−1), and high nitrogen (N3, 480 kg ha−1). The results indicated that in the subtending leaves in upper fruiting branches, chlorophyll content, protein content, and peroxidase (POD) activity dramatically increased with nitrogen application, reaching the highest under the moderate nitrogen treatment. The physiological characters in the seeds had the same trends as in the subtending leaves. Furthermore, the moderate nitrogen rate (240 kg ha−1) had a favorable yield and quality. Our results supported that a moderate nitrogen rate (240 kg ha−1) could coordinate the source–sink growth of cotton in the late stage, enhance the yield and fiber quality, and decrease the cost of fertilizer in the Yellow River Basin of China and other similar ecological areas.

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