AIMS Geosciences, 2018, 4(3): 166-179. doi: 10.3934/geosci.2018.3.166

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Assessment of irrigation shortfall using WATHNET in the Otago region of New Zealand

National Institute of Water and Atmospheric Research, Christchurch, New Zealand

Knowledge of the likely rainfall and river flow for a coming season can improve management of an overall water resources system without unduly compromising either the environmental or productive behaviour of the system. The objective of this study has been to assess the probability of irrigation demand shortfalls, i.e. soil moisture deficits, for a typical “run of the river” irrigation scheme so as to identify the duration and severity of potential shortfalls. In this study a multi-objective linear programming tool WATHNET has been used to build and run a model of the irrigation scheme. The focus of this study has been on how to use predictions of 3-monthly rainfall and temperature to estimate potential daily water available for irrigation. The method uses Monte-Carlo simulations, to produce multiple replicates of equally likely sequences of river flows, rainfall and potential evaporation values. A sub-set of the equally likely sequences is then selected using prediction information of the likely seasonal climate outlook from NIWA’s Climate Update. The selected sequences, which are biased towards the seasonal climate prediction, are then used as inputs to multiple model runs. By using the output from all the “biased” model runs a probability distribution can be made of water availability for irrigation. The methodology has been demonstrated using the Shag River Irrigation Scheme located in the Otago region of New Zealand. The results compare the predicted soil moisture variation over two three-month periods with retrospective simulations based on the observed rainfalls, river flows and potential evaporation values. Results suggest that WATHNET can simulate 3-month soil moisture dynamics. In order to develop WATHNET as a tool to assess probabilities of irrigation shortfall it needs to be validated using measurements of soil moisture variations over an irrigation season at sites with different soil types.
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© 2018 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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