scholarly journals Responses of Hydrological Processes under Different Shared Socioeconomic Pathway Scenarios in the Huaihe River Basin, China

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1053
Author(s):  
Yuan Yao ◽  
Wei Qu ◽  
Jingxuan Lu ◽  
Hui Cheng ◽  
Zhiguo Pang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Climate Models ◽  
Global Climate Models ◽  
Hydrological Response ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Infiltration Capacity ◽  
Change Analysis ◽  
Average Annual Runoff

The Coupled Model Intercomparison Project Phase 6 (CMIP6) provides more scenarios and reliable climate change results for improving the accuracy of future hydrological parameter change analysis. This study uses five CMIP6 global climate models (GCMs) to drive the variable infiltration capacity (VIC) model, and then simulates the hydrological response of the upper and middle Huaihe River Basin (UMHRB) under future shared socioeconomic pathway scenarios (SSPs). The results show that the five-GCM ensemble improves the simulation accuracy compared to a single model. The climate over the UMHRB likely becomes warmer. The general trend of future precipitation is projected to increase, and the increased rates are higher in spring and winter than in summer and autumn. Changes in annual evapotranspiration are basically consistent with precipitation, but seasonal evapotranspiration shows different changes (0–18%). The average annual runoff will increase in a wavelike manner, and the change patterns of runoff follow that of seasonal precipitation. Changes in soil moisture are not obvious, and the annual soil moisture increases slightly. In the intrayear process, soil moisture decreases slightly in autumn. The research results will enhance a more realistic understanding of the future hydrological response of the UMHRB and assist decision-makers in developing watershed flood risk-management measures and water and soil conservation plans.

Soil Moisture Inversion Based on AMSR-E and MODIS Data Fusion: A Case Study of Huaihe River Basin

2014 ◽  
Vol 716-717 ◽  
pp. 1064-1067
Author(s):  
Jing Wen Xu ◽  
Yu Peng Wang ◽  
Jun Fang Zhao ◽  
Fei Yu Pu ◽  
Peng Wang
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Data Fusion ◽  
River Basin ◽  
Surface Condition ◽  
Remote Sensing Data ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Sensing Data ◽  
Modis Data

In this paper, the correlation between fused data and original data, the measured soil and the precipitation data over Huaihe river basin by exploring the inversion of soil moisture from the time and space based on the method of multi-source remote sensing data fusion has been studied. In order to fuse the AMSR-E data which is all-day and all-weather and can penetrate the earth surface to some extent, with the MODIS data that can reflect the surface condition and temperature characteristics, the method of wavelet fusion was carried out in MATLAB. The conclusions of this study are listed as follows: (1) the inversion result of the fused data based on AMSE-E and MODIS is much better than a single remote sensing data inversion; (2) the fused data based on AMSE-E and MODIS is sensitive to soil moisture change trend when the seasons alternated every year, especially in the spring, summer and autumn.

Construction of Drought Indices Based on Passive Microwave Remote Sensing AMSR-E Data over Huaihe River Basin

2013 ◽  
Vol 433-435 ◽  
pp. 1813-1816
Author(s):  
Jing Wen Xu ◽  
Peng Wang ◽  
Jun Fang Zhao ◽  
Shuang Liu
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
River Basin ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Impact Factors ◽  
Drought Indices ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Passive Microwave Remote Sensing

On the basis of previous work, this paper aims to build several proper drought indices based on the basic computation for the band information of passive microwave remote sensing AMSR-E data in Huaihe river basin. Compared with measured soil moisture, optimal drought indices have been selected to explore the spatio-temporal variation laws of drought conditions and its impact factors. The results indicate that there are satisfactory negative correlations between MPDIs (Microwave Polarization Difference Index) and observed soil moisture on the whole, which means the more negative the index is, the more serious the drought will be. Besides, MPDIs at frequency 69GHz and 187GHz calculated by AMSR-E brightness temperature data are much closer to the variation trend of soil moisture than those obtained from other bands.

Construction of Drought Indices from Passive Microwave Remote Sensing AMSR-E Data in Huaihe River Basin

2013 ◽  
Vol 397-400 ◽  
pp. 2503-2506
Author(s):  
Rui Wang ◽  
Jing Wen Xu ◽  
Dan Wang ◽  
Xing Mei Xie ◽  
Peng Wang
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
River Basin ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Drought Indices ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Passive Microwave Remote Sensing ◽  
Spatio Temporal

On the basis of previous work, this paper aims to build several proper drought indices based on passive microwave remote sensing AMSR-E data in Huaihe River Basin. Compared with measured soil moisture, optimal drought indices have been selected to explore the spatio-temporal variation of drought conditions. The results indicate that there are satisfactory negative correlations between MPDIs (Microwave Polarization Index) and observed soil moisture. Moreover, MPDIs calculated by bands of 69GHz and 187GHz are much closer to variation trend of soil moisture than those obtained by other bands.

Validation of AMSR-E Soil Moisture Retrievals over Huaihe River Basin, in China

2014 ◽  
Vol 507 ◽  
pp. 855-858 ◽  
Author(s):  
Xing Mei Xie ◽  
Jing Wen Xu ◽  
Jun Fang Zhao ◽  
Shuang Liu ◽  
Peng Wang
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Temporal Dynamics ◽  
Absolute Error ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Earth Observing System ◽  
X Band ◽  
Precipitation Events

The two soil moisture retrieval methods based on the Advanced Microwave Scanning Radiometer of the Earth Observing System (AMSR-E) data, the standard algorithm by NASA and Land Parameter Retrieval Model (LPRM) have been validated at Xuchang site in Huaihe River basin, in China. The NASA dataset fails to capture main fluctuations of soil moisture, while the LPRM exhibits stronger agreement with the temporal dynamics and precipitation events associated with in situ soil moisture. The LPRM X-band product over ascending pass performs best with correlation coefficient value of 0.42, root mean square error ranging from 0.18 and mean absolute error of 0.14. Generally, the useful soil moisture information can be extracted over HRB from AMSR-E passive microwave data.

scholarly journals Development and application of a short- /long-term composited drought index in the upper Huaihe River basin, China

2015 ◽  
Vol 369 ◽  
pp. 103-108
Author(s):  
M. Yu ◽  
Q. Li ◽  
G. Lu ◽  
H. Wang ◽  
P. Li
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Drought Index ◽  
The Self ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Short Term

Abstract. Accurate and reliable drought monitoring is of primary importance for drought mitigation and reduction of social-ecological vulnerability. The aim of the paper was to propose a short-term/long-term composited drought index (CDI) which could be widely used for drought monitoring and early warning in China. In the study, the upper Huaihe River basin above the Xixian gauge station, which has been hit by severe droughts frequently in recent decades, was selected as the case study site. The short-term CDI was developed by the Principle Component Analysis of the self-calibrating Palmer Drought Severity Index (sc-PDSI), the 1- and 3-month Standardized Precipitation Evapotranspiration Index (SPEI), Z Index (ZIND), the Soil Moisture Index (SMI) with the long-term CDI being formulated by use of the self-calibrating Palmer Hydrology Drought Index (sc-PHDI), the 6-, 12-, 18- and 24-month SPEI, the Standardized Streamflow Index (SSI), the SMI. The sc-PDSI, the PHDI, the ZIND, the SPEI on a monthly time scale were calculated based on the monthly air temperature and precipitation, and the monthly SMI and SSI were computed based on the simulated soil moisture and runoff by the distributed Xinanjiang model. The thresholds of the short-term/long-term CDI were determined according to frequency statistics of different drought indices. Finally, the feasibility of the two CDIs was investigated against the scPDSI, the SPEI and the historical drought records. The results revealed that the short-term/long-term CDI could capture the onset, severity, persistence of drought events very well with the former being better at identifying the dynamic evolution of drought condition while the latter better at judging the changing trend of drought over a long time period.

scholarly journals Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Assessment Tool ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Data ◽  
The Future ◽  
The Impact ◽  
Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

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