Regulated rivers in India: research progress and future directions

Pradhan, Chandan; Chembolu, Vinay; Bharti, Rishikesh; Dutta, Subashisa

doi:10.1080/09715010.2021.1975319

Cited by 12 publications

(5 citation statements)

References 87 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, it governs the grain size distribution of the sediment material and its conveyance to a bar head, which influences the size and stability criteria of a bar. Depending upon the hydraulic regime and reach parameters, the river bed configuration (bed roughness) also provides varied resistance to the flow, which also dissipates a substantial amount of energy (Dubey et al, 2020; Pradhan, Chembolu, Bharti, & Dutta, 2021). According to Dubey et al (2020), the channel has reduced roughness during the monsoon season compared to the non‐monsoon season, which results in a steady river morphology in the course of monsoon period.…”

Section: Energy Dissipation Processes In a Highly Braided River Systemmentioning

confidence: 99%

How dynamic is the Brahmaputra? Understanding the process–form–vegetation interactions for hierarchies of energy dissipation

et al. 2022

Self Cite

View full text Add to dashboard Cite

The spatio‐temporal heterogeneity in process–form–vegetation interactions has enabled the Brahmaputra river system to dissipate the fluvial energy at hierarchical scales. The present review article synthesizes the knowledge on braided rivers and an extensive review of the bio‐morphological processes in the Brahmaputra River. In addition, field investigated datasets along with geo‐spatial imageries and Google Earth Engine computed fluvial information are integrated to conceptualize and understand the complex underlying processes in the river. The review can be further used to propose rejuvenation frameworks and research directions concerning the implication of hierarchical energy dissipation potential in the Brahmaputra River.

show abstract

Section: Energy Dissipation Processes In a Highly Braided River Systemmentioning

confidence: 99%

How dynamic is the Brahmaputra? Understanding the process–form–vegetation interactions for hierarchies of energy dissipation

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Indeed, c max , the maximum soil storage capacity, takes a value of 5900 mm in Rajoli and 2500 mm in Satrapur, while the lowest value it takes is 800 mm in Wairagarh. Formal quantification of reservoir effects is complicated, as the interaction of each reservoir and catchment is unique in India [51]. Finally, equifinality (multiple ways to achieve the same answer) may mean that the same KGE' can be achieved by more than one parameter set.…”

Section: Lumped Sub-catchment Modelingmentioning

confidence: 99%

Flood Frequency Estimation in Data-Sparse Wainganga Basin, India, Using Continuous Simulation

Vesuviano

Griffin

Stewart

2022

Water

View full text Add to dashboard Cite

Monsoon-related extreme flood events are experienced regularly across India, bringing costly damage, disruption and death to local communities. This study provides a route towards estimating the likely magnitude of extreme floods (e.g., the 1-in-100-year flood) at locations without gauged data, helping engineers to design resilient structures. Gridded rainfall and evapotranspiration estimates were used with a continuous simulation hydrological model to estimate annual maximum flow rates at nine locations corresponding with river flow gauging stations in the Wainganga river basin, a data-sparse region of India. Hosking–Wallis distribution tests were performed to identify the most appropriate distribution to model the annual maxima series, selecting the Generalized Pareto and Pearson Type III distributions. The L-moments and flood frequency curves of the modeled annual maxima were compared to gauged values. The Probability Distributed Model (PDM), properly calibrated to capture the dynamics of peak flows, was shown to be effective in approximating the Generalized Pareto distribution for annual maxima, and may be useful in modeling peak flows in areas with sparse data. Confidence in the model structure, parameterization, input data and catchment representation build confidence in the modeled flood estimates; this is particularly relevant if the method is applied in a location where no gauged flows exist for verification.

show abstract

“…Around the globe, anthropogenic stresses in terms of flow-sediment regulation, deforestation, channelization, and clearing of (instream) riparian vegetation have created both on-site and legacy effects in the fluvial systems 1 – 6 . The geomorphic impacts of such disturbances can vary from localised scour and incision to large scale transformation in channel patterns 7 – 12 .…”

Section: Introductionmentioning

confidence: 99%

“…In India, peninsular rivers are an integral part of the water-food-energy nexus, supporting millions of people through agriculture, industries, and flood control 6 . However, these river basins also have a large history of receiving intense anthropogenic stresses for two centuries.…”

Section: Introductionmentioning

confidence: 99%

“…For example, an extensive loss of forest cover was reported for the central-east regions of India in 1880–1960 65 . The dam-building activity was also at its peak during 1970–1990, and numbers of the small height large dams and mega-dams of national importance had increased by three to four times 6 . Such large scale anthropogenic disturbances combined with localised fluvial disturbances like sand mining, instream (riparian) vegetation loss, and channelization have instigated geomorphic and (bio)ecological adjustments along the fluvial systems 66 – 69 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A process-based recovery indicator for anthropogenically disturbed river system

Pradhan

Padhee

Bharti

et al. 2022

Sci Rep

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Regulated rivers in India: research progress and future directions

Cited by 12 publications

References 87 publications

How dynamic is the Brahmaputra? Understanding the process–form–vegetation interactions for hierarchies of energy dissipation

How dynamic is the Brahmaputra? Understanding the process–form–vegetation interactions for hierarchies of energy dissipation

Flood Frequency Estimation in Data-Sparse Wainganga Basin, India, Using Continuous Simulation

A process-based recovery indicator for anthropogenically disturbed river system

Contact Info

Product

Resources

About