Spatio-temporal variability of streamflow in the Huaihe River Basin, China: climate variability or human activities?

Pan, Zharong; Ruan, Xinbo; Qian, Mingkai; Hua, Jian; Shan, Nan; Xu, Jing

doi:10.2166/nh.2017.155

Cited by 27 publications

(12 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The HuaiRB is situated in the climate transition zone between the humid southern region of China and the semihumid northern region and is chiefly characterized by monsoonal weather conditions (Pan et al 2017). Note that, following Yong et al (2016), the division between humid and semihumid climate is based on a threshold of 800 mm for mean annual precipitation (as shown in Fig.…”

Section: A Study Areamentioning

confidence: 97%

The Effect of Spatiotemporal Resolution Degradation on the Accuracy of IMERG Products over the Huai River Basin

Lü

Crow

et al. 2020

Journal of Hydrometeorology

View full text Add to dashboard Cite

The rapid development of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) precipitation product provides new opportunities for a wide range of Earth system and natural hazard applications. Spatiotemporal averaging is a common method for IMERG users to acquire suitable resolutions specific to their research or application purpose and has a direct impact on the overall quality of IMERG precipitation estimates. Here, three different IMERG, version 06 (V06), latency run products (i.e., early, late, and final) are assessed against a ground-based benchmark along a continuous series of spatiotemporal resolutions over the Huai River basin (HuaiRB) between June 2014 and May 2017. In general, IMERG products better capture the spatial pattern of precipitation, and demonstrate better reliability, in the southern portion of the HuaiRB relative to its northern region. Furthermore, the degradation of spatiotemporal resolution is associated with better rain/no-rain determination and the consistent improvement of rainfall product performance metrics. This improvement is more pronounced for IMERG products at fine spatiotemporal resolution. However, due to the presence of autocorrelated errors, the performance improvement associated with the degradation of spatiotemporal resolution is less than theoretical expectations assuming purely uncorrelated errors. Component analysis indicates that while both temporal and spatial aggregation do not mitigate temporally autocorrelated errors, temporal averaging can remove spatially autocorrelated error. Hence, temporal averaging is found to be more effective than spatial averaging for improving the quality of IMERG products. These results will inform users of the reliability of IMERG products at different spatiotemporal scales and assist in unifying former disparate validation assessments applied at different scales within the literature.

show abstract

Section: A Study Areamentioning

confidence: 97%

The Effect of Spatiotemporal Resolution Degradation on the Accuracy of IMERG Products over the Huai River Basin

Lü

Crow

et al. 2020

Journal of Hydrometeorology

View full text Add to dashboard Cite

show abstract

“…The climate in this area is generally humid and hot in summer while dry and cold in winter. The southern part of Huai River basin belongs to the humid subtropical climate zone, where the climate is mild, with obvious sign of climate transition between North and South [ 41 ]. The geographical mapping of the Huai River basin is shown in Figure 3 .…”

Section: Case Studymentioning

confidence: 99%

Assessing Water Resources Vulnerability by Using a Rough Set Cloud Model: A Case Study of the Huai River Basin, China

Chen

Feng

Zhang

2018

Entropy

View full text Add to dashboard Cite

Assessing water resources vulnerability is the foundation of local water resources management. However, as one of the major water systems in China, there is no existing evaluation index system that can effectively assess water resource vulnerability for the Huai River basin. To address this issue, we identified key vulnerability factors, constructed an evaluation index system, and applied such system to evaluate water resources vulnerability for the Huai River basin empirically in this paper. Specifically, our evaluation index system consists of 18 indexes selected from three different aspects: water shortage, water pollution, and water-related natural disaster. Then, the improved blind deletion rough set method was used to reduce the size of the evaluation index while keep the evaluation power. In addition, the improved conditional information entropy rough set method was employed to calculate the weights of evaluation indexes. Based on the reduced index system and calculated weights, a rough set cloud model was applied to carry out the vulnerability evaluation. The empirical results show that the Huai River basin water resources were under severe vulnerability conditions for most of the time between 2000 and 2016, and the Most Stringent Water Resources Management System (MS-WRMS) established in 2012 did not work effectively as expected.

show abstract

“…The first one is the Comparison of Basin Experiment, which is an effective approach and very suitable for studies in small watersheds to eliminate the influence of climate change (Gao and Ruan, 2018). The second one is the Statistical Method based on the analysis of hydrometerological data series (Gao et al, 2015;Pan et al, 2018;Piao et al, 2010). It is a pure mathematical tool without considering the spatial heterogeneity and mechanisms of LULC change and climate change on hydrological processes, although with relatively simple operation.…”

Section: Introductionmentioning

confidence: 99%

Impacts of climate change and LULC change on runoff in the Jinsha River Basin

Chen

Zhang

et al. 2020

J. Geogr. Sci.

View full text Add to dashboard Cite

The climate change and Land Use/Land Cover (LULC) change both have an important impact on the rainfall-runoff processes. How to quantitatively distinguish and predict the impacts of the above two factors has been a hot spot and frontier issue in the field of hydrology and water resources. In this research, the SWAT (Soil and Water Assessment Tool) model was established for the Jinsha River Basin, and the method of scenarios simulation was used to study the runoff response to climate change and LULC change. Furthermore, the climate variables exported from 7 typical General Circulation Models (GCMs) under RCP4.5 and RCP8.5 emission scenarios were bias corrected and input into the SWAT model to predict runoff in 2017-2050. Results showed that: (1) During the past 57 years, the annual average precipitation and temperature in the Jinsha River Basin both increased significantly while the rising trend of runoff was far from obvious. (2) Compared with the significant increase of temperature in the Jinsha River Basin, the LULC change was very small. (3) During the historical period, the LULC change had little effect on the hydrological processes in the basin, and climate change was one of the main factors affecting runoff. (4) In the context of global climate change, the precipitation, temperature and runoff in the Jinsha River Basin will rise in 2017-2050 compared with the historical period. This study provides significant references to the planning and management of large-scale hydroelectric bases at the source of the Yangtze River.

show abstract

Spatio-temporal variability of streamflow in the Huaihe River Basin, China: climate variability or human activities?

Cited by 27 publications

References 25 publications

The Effect of Spatiotemporal Resolution Degradation on the Accuracy of IMERG Products over the Huai River Basin

The Effect of Spatiotemporal Resolution Degradation on the Accuracy of IMERG Products over the Huai River Basin

Assessing Water Resources Vulnerability by Using a Rough Set Cloud Model: A Case Study of the Huai River Basin, China

Impacts of climate change and LULC change on runoff in the Jinsha River Basin

Contact Info

Product

Resources

About