Title

Method of last resort (MOLR) long term average annual recharge estimates 

Alternate title

MOLR_RECHARGE 

Supplemental Information

Related Documents: None See Geoscience Australia metadata record at: https://www.ga.gov.au/products/servlet/controller?event=GEOCAT_DETAILS&catno=71607 

Status

Completed  

Code

4283 

Maintenance and update frequency

Not planned  

Title

DIGITAL: ESRI GRID, ESRI Shapefile 3 

Topic category

• Inland waters
• Geoscientific information

Use limitation

General 

Classification

Unclassified  

Statement

Dataset Source: This dataset has been extracted for Victoria from a database of approx. 4400 recharge and/or deep drainage estimates collated from 172 studies. Crosbie et al. (2010B) used a sub-set of data from this database to determine whether simple empirical relationships could be found that relate groundwater recharge to nationally available datasets and hence whether they can be used to estimate recharge in data poor areas in a scientifically defensible way. It was found that vegetation and soil type were critical determinants in forming relationships between average annual rainfall and average annual recharge, whereas climate zones (Köppen-Geiger climate classification and aridity index) and surface geology (lithology) were not found to be significant determinants. The MOLR further simplified the relationships developed by Crosbie et al. (2010B) by combining the perennial and tree vegetation types due to a lack of data under these vegetation types. The soils groupings used by Crosbie et al. (2010B) have been retained for the MOLR, these are: Vertosols (VE); Calcarosols (CA), Chromosols (CH), Kurosols (KU) and Sodosols (SO); Podosols (PO); Rudosols (RU), Kandasols (KA) and Tenosols (TE); Ferrosols (FE), Dermosols (DE), Hydrosols (HY) and Organosols (OR). No estimate of recharge is possible using the MOLR from the last soils group (FE,DE,HY,OR) due to a lack of field studies required to develop the relationships. The relationships that were developed between recharge and mean annual rainfall, soil order and vegetation type used a two parameter regression model R =10^aP+b where a and b are the fitting parameters from a least squares regression between annual average rainfall (P) and the logarithm of annual average recharge (R). For more information on the relationship observed in the outputs from average annual rainfall and average annual recharge for the combination of soil and vegetation groups, the reader is referred to Section 2.3.3 in the document: http://www.clw.csiro.au/publications/waterforahealthycountry/2011/wfhc-recharge-discharge-scientific-guide.pdf. Dataset Originality: Derived 

Description

Collection Method: See above 

Description

Source description not available 

Description

See above 

Classification

Unclassified  

Attribute Quality

Comments

Not Known 

Positional Accuracy

Comments

Not Known 

Conceptual Consistency

Comments

Not Known 

Missing Data

Comments

Victoria 

Excess Data