Dynamics and scales of transmission losses in dryland river systems: a meta-analysis. Issue 2 (3rd July 2022)

• Record Type: Journal Article
• Authors: Mujere, Never; Masocha, Mhosisi; Makurira, Hodson; Mazvimavi, Dominic
• Is Part Of: Australian journal of water resources. Volume 26:Issue 2(2022)
• Page Start: 227
• Page End: 241
• Publication Date: 2022-07-03
• Subjects: Drylands -- meta-analysis -- river channel transmission losses -- regression equations -- differential equations -- flow routing -- field experiments -- water balance -- spatial models; Water resources development -- Australia -- Periodicals; Hydrology -- Australia -- Periodicals; Water-supply -- Australia -- Periodicals; 627.099405
• DOI: 10.1080/13241583.2021.1996680
• Languages: English
• ISSNs: 1324-1583

Abstract

ABSTRACT: In this paper, 245 studies were reviewed to understand approaches used for estimating river channel transmission losses. Findings indicate that regression equations, differential equations, flow routing, experimental approaches and water balances are most widely used. Geographic Information Systems are becoming a convenient framework to display model results showing spatial variability of losses. In the United States, regression equations and experimental approaches involving controlled releases are widely used to assess transmission losses whereas in the dryland regions of Australia, water balance and flow routing approaches are popular. In Africa and Asia, regression equations and water balances are common approaches to estimate transmission losses. By using regression equations on data pooled from studies done in different dryland regions of the world, statistically significant (p<0.05) relationships were observed between transmission loss volume and, reach length, inflow, flow contributing area and runoff coefficient. Overall, the review underscores the importance of channel and catchment characteristics in shaping the dynamics of transmission losses. Two main limitations of the current approaches are that they are site-specific and require high amounts of data not always available in dryland regions due to sparse network of monitoring stations. The review also highlights existing knowledge gaps and future research needs.