Semantic Scholar Open Access 2024 4 sitasi

Developing a model to assess the impact of farm dams and irrigation for data-scarce catchments

Andrew Watson A. Künne C. Birkel Jodie Miller S. Kralisch

Abstrak

ABSTRACT Productive agricultural supply chains require the support of functional ecosystems, but intense agricultural practices change local hydrological systems (e.g. river diversion). In this study, the impact of farm dams was assessed for the Verlorenvlei catchment, a sensitive ecosystem currently under a state of hydrological change in South Africa. We developed a new module for the Jena Adaptable Modelling System (JAMS)/J2000 rainfall–runoff model to assess the streamflow impact from the points of abstraction, losses during storage and irrigation. The model achieved a satisfactory streamflow calibration with efficiencies Nash Sutcliffe Efficiency (NSE, logNSE) of 0.52 and 0.51. The irrigated area reduced simulated streamflow by 12 to 19%. The results from the study agree with remote sensed evapotranspiration, measured lake surface water levels and streamflow, but uncertainty remains in the total simulated dam evaporation. While many catchments lack the data required for a detailed irrigation impact assessment, this approach considers total water use, dam storage to area relationships and general farming practices.

Penulis (5)

A

Andrew Watson

A

A. Künne

C

C. Birkel

J

Jodie Miller

S

S. Kralisch

Format Sitasi

Watson, A., Künne, A., Birkel, C., Miller, J., Kralisch, S. (2024). Developing a model to assess the impact of farm dams and irrigation for data-scarce catchments. https://doi.org/10.1080/02626667.2024.2331790

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Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Total Sitasi
Sumber Database
Semantic Scholar
DOI
10.1080/02626667.2024.2331790
Akses
Open Access ✓