Changjiang Ren
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Changjiang Ren has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Changhai Qin
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, China
1 shared publication - Chenhua Liu
School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, China
1 shared publication Haihong Li
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research Beijing China
1 shared publication- Haomin Cui
Base of the State Laboratory of Urban Environmental Processes and Digital Modeling, Capital Normal University, Beijing, China
1 shared publication Jiaguo Gong
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research Beijing China
1 shared publicationJianhua Wang
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research Beijing China
1 shared publication
Latest Publications
- 22 September 2025
- Published by Springer Nature in Cluster Computing
- Vol. 28 (13) , 1-50
Multi-strategy evolutionary enhanced particle swarm optimizer with adaptive morphology for engineering example
- 22 September 2025
- Published by Springer Nature in Cluster Computing
- Vol. 28 (13) , 1-50
Multi-strategy evolutionary enhanced particle swarm optimizer with adaptive morphology for engineering example
- Top Cited Papers
- 4 July 2023
- Published by Elsevier in Expert Systems with Applications
- Vol. 233
Great Wall Construction Algorithm: A novel meta-heuristic algorithm for engineer problems
- 4 July 2023
- Published by Elsevier in Expert Systems with Applications
- Vol. 233
Top Cited PapersGreat Wall Construction Algorithm: A novel meta-heuristic algorithm for engineer problems
- 10 April 2020
- Published by Wiley in Hydrological Processes
- Vol. 34 (12) , 2793-2809
Application of a water infiltration model for simulating water repellency of humus soil
One‐dimensional infiltration experiments were conducted using hydrophilic and water‐repellent soils from the Guishui River Basin to study the effects of soil water repellency on cumulative infiltration (CI) and the infiltration rate (IR). The test results show that, for the hydrophilic soil (HS) sample, CI increases monotonously with time and IR decreases monotonously. For the water‐repellent soil (W‐RS), however, the following characteristics were observed: (a) There is an inflection point in CI and a sudden increase in IR. Larger values of the initial soil water content produce an earlier and more significant inflection point in CI, and a larger peak value of IR. (b) The post‐peak stable IR is greater than the pre‐peak value, ignoring the beginning of rapid infiltration, and the overall IR presents a single peak. The applicability of various water infiltration models was analysed for the two soil types. Numerical analysis suggests the following conclusions: (a) For both HS and W‐RS, the Kostiakov function, Gamma function, and Beta function (BF) models exhibit good applicability. (b) For W‐RS, the Gauss function model not only reflects the monotonous decrease in IR, but also produces a steady IR in the initial stage, a gradual increase before the peak value, and a gradual decrease after the peak value. Similarly, the BF model reflects the monotonous decrease in IR. A piecewise BF reproduces the U‐shaped change in rapid infiltration before the inflection point, as well as the gradual increase and right‐skewed distribution curve of W‐RS infiltration before and after the inflection point. The BF model achieves the best simulation accuracy and has the widest applicability.
- 10 April 2020
- Published by Wiley in Hydrological Processes
- Vol. 34 (12) , 2793-2809
Application of a water infiltration model for simulating water repellency of humus soil
One‐dimensional infiltration experiments were conducted using hydrophilic and water‐repellent soils from the Guishui River Basin to study the effects of soil water repellency on cumulative infiltration (CI) and the infiltration rate (IR). The test results show that, for the hydrophilic soil (HS) sample, CI increases monotonously with time and IR decreases monotonously. For the water‐repellent soil (W‐RS), however, the following characteristics were observed: (a) There is an inflection point in CI and a sudden increase in IR. Larger values of the initial soil water content produce an earlier and more significant inflection point in CI, and a larger peak value of IR. (b) The post‐peak stable IR is greater than the pre‐peak value, ignoring the beginning of rapid infiltration, and the overall IR presents a single peak. The applicability of various water infiltration models was analysed for the two soil types. Numerical analysis suggests the following conclusions: (a) For both HS and W‐RS, the Kostiakov function, Gamma function, and Beta function (BF) models exhibit good applicability. (b) For W‐RS, the Gauss function model not only reflects the monotonous decrease in IR, but also produces a steady IR in the initial stage, a gradual increase before the peak value, and a gradual decrease after the peak value. Similarly, the BF model reflects the monotonous decrease in IR. A piecewise BF reproduces the U‐shaped change in rapid infiltration before the inflection point, as well as the gradual increase and right‐skewed distribution curve of W‐RS infiltration before and after the inflection point. The BF model achieves the best simulation accuracy and has the widest applicability.