An Eco-Hydrological Model-Based Assessment of the Impacts of Soil and Water Conservation Management in the Jinghe River Basin, China

Peng, Hui; Jia, Yangwen; Tague, Christina; Slaughter, Peter

doi:10.3390/w7116301

Cited by 20 publications

(19 citation statements)

References 31 publications

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“…The basin has a typical continental climate, and lies in the semihumid and semi-arid transitional zone [41]. The Weihe River (hereafter WR) provides the water supply for 9300 km 2 of fertile fields in the Guanzhong Plain, and more than 61% of the Shaanxi Province's population [42].…”

Section: Study Areamentioning

confidence: 99%

Maximum Entropy-Copula Method for Hydrological Risk Analysis under Uncertainty: A Case Study on the Loess Plateau, China

Guo

Chang

Wang

et al. 2017

Entropy

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Copula functions have been extensively used to describe the joint behaviors of extreme hydrological events and to analyze hydrological risk. Advanced marginal distribution inference, for example, the maximum entropy theory, is particularly beneficial for improving the performance of the copulas. The goal of this paper, therefore, is twofold; first, to develop a coupled maximum entropy-copula method for hydrological risk analysis through deriving the bivariate return periods, risk, reliability and bivariate design events; and second, to reveal the impact of marginal distribution selection uncertainty and sampling uncertainty on bivariate design event identification. Particularly, the uncertainties involved in the second goal have not yet received significant consideration. The designed framework for hydrological risk analysis related to flood and extreme precipitation events is exemplarily applied in two catchments of the Loess plateau, China. Results show that (1) distribution derived by the maximum entropy principle outperforms the conventional distributions for the probabilistic modeling of flood and extreme precipitation events; (2) the bivariate return periods, risk, reliability and bivariate design events are able to be derived using the coupled entropy-copula method; (3) uncertainty analysis highlights the fact that appropriate performance of marginal distribution is closely related to bivariate design event identification. Most importantly, sampling uncertainty causes the confidence regions of bivariate design events with return periods of 30 years to be very large, overlapping with the values of flood and extreme precipitation, which have return periods of 10 and 50 years, respectively. The large confidence regions of bivariate design events greatly challenge its application in practical engineering design.

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Section: Study Areamentioning

confidence: 99%

Maximum Entropy-Copula Method for Hydrological Risk Analysis under Uncertainty: A Case Study on the Loess Plateau, China

Guo

Chang

Wang

et al. 2017

Entropy

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“…Furthermore, 52.3% of the total studies have been applied for study areas less than 100 km 2 and time windows less than 25 years account. To date, few studies have applied RHESSys to a large-scale watershed, e.g., there are only two studies for the areas that exceed 10,000 km 2 [9,26]. RHESSys has been applied to a wide range of spatial and temporal scales as shown in Figure 7.…”

Section: Research Trends and Characteristicsmentioning

confidence: 99%

The Regional Hydro-Ecological Simulation System for 30 Years: A Systematic Review

Chen

Liu

et al. 2020

Water

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As the Regional Hydro-Ecological Simulation System (RHESSys) is a tool to simulate the interactions between ecological and hydrological processes, many RHESSys-based studies have been implemented for sustainable watershed management. However, it is crucial to review a RHESSys updating history, pros, and cons for further improving the RHESSys and promoting ecohydrological studies. This paper reviewed the progress of ecohydrological studies employing RHESSys by a bibliometric analysis that quantitatively analyzed the characteristics of relevant studies. In addition, we addressed the main application progress, parameter calibration and validation methods, and uncertainty analysis. We found that since its release in 1993, RHESSys has been widely applied for basins (<100 km2) within mainly seven biomes. The RHESSys model has been applied for evaluating the ecohydrological responses to climate change, land management, urbanization, and disturbances, as well as water quality and biogeochemical cycle. While most studies have paid their attention on climate change, the focus has shifted to the application for land management in recent years. This study also identified many challenges in RHESSys such as the inaccessible data and parameters, oversimplified calibration approach, few applications for large-scale watersheds, and limited application fields. Therefore, this study proposed a set of suggestions to overcome the limitations and challenges: (1) Developing a new approach for parameter acquisition and calibration from multi-source data, (2) improving the applicability for a large-scale basin, and (3) extending the scope of application fields. We believe RHESSys can improve the understandings of human–environment relationships and the promotion of sustainable watersheds development.

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“…In Jinghe River Basin, a large number of ecological restoration projects has been implemented in the past 30 years since the 1980s. However, these costly efforts yielded little success during the first 20 years (Peng et al, 2015). In the past 10 years, vegetation restoration has begun to achieve certain effects, and the average summer NDVI has increased from 0.4 in 2000 to 0.7 in 2013.…”

Section: Study Areamentioning

confidence: 99%

Impact of large-scale vegetation restoration project on summer land surface temperature on the Loess Plateau, China

Zhao

Wang

et al. 2018

J. Arid Land

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A large-scale afforestation project has been carried out since 1999 in the Loess Plateau of China. However, vegetation-induced changes in land surface temperature (LST) through the changing land surface energy balance have not been well documented. Using satellite measurements, this study quantified the contribution of vegetation restoration to the changes in summer LST and analyzed the effects of different vegetation restoration patterns on LST during both daytime and nighttime. The results show that the average daytime LST decreased by 4.3°C in the vegetation restoration area while the average nighttime LST increased by 1.4°C. The contributions of the vegetation restoration project to the changes in daytime LST and nighttime LST are 58% and 60%, respectively, which are far greater than the impact of climate change. The vegetation restoration pattern of cropland (CR) converting into artificial forest (AF) has a cooling effect during daytime and a warming effect at nighttime, while the conversion of CR to grassland has an opposite effect compared with the conversion of CR to AF. Our results indicate that increasing evapotranspiration caused by the vegetation restoration on the Loess Plateau is the controlling factor of daytime LST change, while the nighttime LST change is affected by soil humidity and air humidity.

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An Eco-Hydrological Model-Based Assessment of the Impacts of Soil and Water Conservation Management in the Jinghe River Basin, China

Cited by 20 publications

References 31 publications

Maximum Entropy-Copula Method for Hydrological Risk Analysis under Uncertainty: A Case Study on the Loess Plateau, China

Maximum Entropy-Copula Method for Hydrological Risk Analysis under Uncertainty: A Case Study on the Loess Plateau, China

The Regional Hydro-Ecological Simulation System for 30 Years: A Systematic Review

Impact of large-scale vegetation restoration project on summer land surface temperature on the Loess Plateau, China

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