Groundwater recharge prediction for broadscale irrigation modelling: a case study in MIA-Main Canal irrigated areas

Makireddi, Surya (2014) Groundwater recharge prediction for broadscale irrigation modelling: a case study in MIA-Main Canal irrigated areas. [USQ Project]


Download (2MB) | Preview


Determining the water balance is a vital element in water resource management. This is particularly important for arid and semi-arid regions in Australia where surface water resources such as rivers and rainfall are less available. Consumption of water is the highest for agricultural purposes in Australia. Due to the importance of conserving water resources in the background of agriculture and climate it is necessary to quantify the water incoming to the system and water outgoing from the system. For this reason, it is required to estimate the amount of groundwater recharge. The project deals with recharge within irrigated areas. The study area chosen is a group of irrigation districts, geographically located within the Murrumbidgee Irrigation Areas (MIA). The MIA is situated in southern-central New South Wales. The study area and the MIA come under semi-arid environment. Agriculture is prevalent in the MIA. The irrigation districts under the study area receive irrigation water diversions from the Main Canal which inturn is diverted from the Murrumbidgee River.

This report describes the application of a newly developed recharge optimisation method for arriving at prediction parameters specific to the study area for estimating groundwater recharge from an irrigated area. The method is developed leading from AWRA-R irrigation model which is developed by Commonwealth Scientific and Industrial Research Organisation (CSIRO). The irrigation model has two components in it: Diversions modelling module and Recharge estimation module. The diversions module is built inorder to estimate irrigation diversions to agricultural farms at a river basin scale. It is simple, can be calibrated and run for long-term simulations quickly. It is designed to generate estimations of diversions even under circumstances of parsimonious data availability. Recharge module, the other component, is a modified form of Overbank flood recharge (OFR) method to estimate groundwater recharge for a given district.

The AWRA-R irrigation model is applied to the study area and the simulated results for groundwater recharge are obtained. These results are further optimised based on factors that influence recharge dominantly in the study area. Simulations are run by varying the input parameters to the irrigation model thus obtaining 840 trial recharge estimations. These recharge values are fitted against a set of collated recharge estimates from previous studies and researches done within the MIA and the lower Murrumbidgee by means of root-mean-square error analysis. The simulation recharge outputs that give the closest fit to the collated data are accepted to be the recharge estimates specific to the study area. The input parameters, Kc and soilCap, applied for that simulation are determined to be prediction parameters, the values of which are 7.78E-07m/sec and 0.105m respectively. The prediction parameters, thus deduced, have been used to estimate recharge for years 1970-2012. From the results of simulated recharge, it is observed that there are several years with no recharge while the maximum recharge is 79.49mm in the year of 1991.

Statistics for USQ ePrint 27246
Statistics for this ePrint Item
Item Type: USQ Project
Item Status: Live Archive
Additional Information: Bachelor of Engineering (Civil) project.
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 - 31 Dec 2021)
Supervisors: Brodie, Ian
Date Deposited: 09 Sep 2015 04:59
Last Modified: 03 Mar 2016 04:16
Uncontrolled Keywords: hydrology; irrigation modelling; CSIRO; overbank flood recharge; OFR; recharge estimates; groundwater recharge; AWRA-R irrigation model; agricultural farms; river basin scale
Fields of Research (2008): 09 Engineering > 0907 Environmental Engineering > 090702 Environmental Engineering Modelling
07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070105 Agricultural Systems Analysis and Modelling
09 Engineering > 0905 Civil Engineering > 090509 Water Resources Engineering
Fields of Research (2020): 40 ENGINEERING > 4011 Environmental engineering > 401199 Environmental engineering not elsewhere classified
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300207 Agricultural systems analysis and modelling
40 ENGINEERING > 4005 Civil engineering > 400513 Water resources engineering

Actions (login required)

View Item Archive Repository Staff Only