Department of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati, 781039, India.
International Water Management Institute, Delhi, India.
Sci Rep. 2022 Jun 20;12(1):10390. doi: 10.1038/s41598-022-14542-x.
The present paper utilizes entropy theory and Google earth engine cloud computing technique to investigate system state and river recovery potential in two large sub-basins of the Mahanadi River, India. The cross-sectional intensity entropy (CIE) is computed for the post-monsoon season (October-March) along the selected reaches. Further, a normalized river recovery indicator (NRRI) is formulated to assess the temporal changes in river health. Finally, NRRI is related to a process-based variable-LFE (low flow exceedance) to comprehend the dominating system dynamics and evolutionary adjustments. The results highlight the existence of both threshold-modulated and filter-dominated systems based on CIE and NRRI variabilities. In addition, the gradual decline in CIE and subsequent stabilization of vegetated landforms can develop an 'event-driven' state, where floods exceeding the low-flow channel possess a direct impact on the river recovery trajectory. Finally, this study emphasizes the presence of instream vegetation as an additional degree of freedom, which further controls the hierarchy of energy dissipation and morphological continuum in the macrochannel settings.
本文利用熵理论和谷歌地球引擎云计算技术，研究了印度马哈纳迪河两个大支流的系统状态和河流恢复潜力。在选定的河段上，计算了后季风季节（10 月至 3 月）的截面强度熵（CIE）。此外，还制定了归一化河流恢复指标（NRRI），以评估河流健康状况的时间变化。最后，将 NRRI 与基于过程的变量-LFE（低流量超标）相关联，以了解占主导地位的系统动态和演化调整。结果表明，基于 CIE 和 NRRI 的变异性，存在阈值调制和滤波器占主导地位的系统。此外，CIE 的逐渐下降和随后植被地貌的稳定化可能会形成一个“事件驱动”的状态，其中超过低流通道的洪水对河流恢复轨迹有直接影响。最后，本研究强调了河流内部植被作为附加自由度的存在，这进一步控制了宏通道环境中能量耗散和形态连续体的层次结构。
