Integrating the spatial variability of water quality and quantity to probabilistically assess groundwater sustainability for use in aquaculture
2013
Aquaculture industries generally extract large amounts of groundwater for the cultivation of fish. To reduce the adverse effects on fish cultivation and groundwater drawdown, this study develops a method that simultaneously considers the spatial variability of groundwater in terms of quality and quantity in order to determine sustainable groundwater use for aquaculture in the Pingtung Plain, Taiwan. Because of limited observation data with high prediction uncertainty, sequential indicator simulation (SIS) was adopted to reproduce the spatial distributions of the main pollutants in groundwater, manganese and ammonium-nitrogen. The corresponding distributions of the groundwater utilization ratio (GUR), which is defined as the ratio showing the volume of groundwater utilization compared to pond water, were determined based on the mass balance of the hydrochemical parameters in the groundwater, surface water, and pond water. Four categories in groundwater utilization—GUR < 0.1 (strictly limited), 0.1 ≦ GUR < 0.5 (minor), 0.5 ≦ GUR < 1 (major), and GUR = 1 (completely used)—were characterized based on estimated probabilities. A safe GUR was selected from a maximum estimation probability of the groundwater categories. SIS was also used to grade the transmissivity fields for gauging the pumping capacity of the aquifers. Finally, for different conditions indicating groundwater quality and quantity, the combinations were delineated spatially to provide decision makers with detailed information which will enable them to wisely select a reliable scheme for groundwater management of fishponds. The analytical results reveal that groundwater can be completely used for fish farming in 6.9 % of aquifers, but should serve as a minor water resource for fishponds in 8.6 % of aquifers.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
27
References
10
Citations
NaN
KQI