Institutional Repository
Technical University of Crete
Technical University of Crete
EN
|
EL
| URI | http://purl.tuc.gr/dl/dias/E998AB7C-781E-45F9-AC55-40CA08D899CE | - |
| Identifier | 10.1007/s10661-012-2527-y | - |
| Identifier | https://link.springer.com/article/10.1007/s10661-012-2527-y | - |
| Language | en | - |
| Extent | 19 pages | en |
| Title | Comparison of stochastic and deterministic methods for mapping groundwater level spatial variability in sparsely monitored basins | en |
| Creator | Varouchakis Emmanouil | en |
| Creator | Βαρουχακης Εμμανουηλ | el |
| Creator | Christopoulos Dionysios | en |
| Creator | Χριστοπουλος Διονυσιος | el |
| Publisher | Springer Verlag | en |
| Description | Δημοσίευση σε επιστημονικό περιοδικό | el |
| Content Summary | In sparsely monitored basins, accurate mapping of the spatial variability of groundwater level requires the interpolation of scattered data. This paper presents a comparison of deterministic interpolation methods, i.e. inverse distance weight (IDW) and minimum curvature (MC), with stochastic methods, i.e. ordinary kriging (OK), universal kriging (UK) and kriging with Delaunay triangulation (DK). The study area is the Mires Basin of Mesara Valley in Crete (Greece). This sparsely sampled basin has limited groundwater resources which are vital for the island's economy; spatial variations of the groundwater level are important for developing management and monitoring strategies. We evaluate the performance of the interpolation methods with respect to different statistical measures. The Spartan variogram family is applied for the first time to hydrological data and is shown to be optimal with respect to stochastic interpolation of this dataset. The three stochastic methods (OK, DK and UK) perform overall better than the deterministic counterparts (IDW and MC). DK, which is herein for the first time applied to hydrological data, yields the most accurate cross-validation estimate for the lowest value in the dataset. OK and UK lead to smooth isolevel contours, whilst DK and IDW generate more edges. The stochastic methods deliver estimates of prediction uncertainty which becomes highest near the southeastern border of the basin. | en |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-11-06 | - |
| Date of Publication | 2012 | - |
| Subject | Biomonitoring (Ecology) | en |
| Subject | Ecological monitoring | en |
| Subject | Environmental quality--Measurement | en |
| Subject | Environmental quality--Monitoring | en |
| Subject | Monitoring, Environmental | en |
| Subject | environmental monitoring | en |
| Subject | biomonitoring ecology | en |
| Subject | ecological monitoring | en |
| Subject | environmental quality measurement | en |
| Subject | environmental quality monitoring | en |
| Subject | monitoring environmental | en |
| Subject | Groundwater--Ecology | en |
| Subject | groundwater ecology | en |
| Bibliographic Citation | E. A. Varouchakis and D. T. Hristopulos, "Comparison of stochastic and deterministic methods for mapping groundwater level spatial variability in sparsely monitored basins", Environmental Monitoring and Assessment, vol. 185, no 1, Feb. 2012. doi: 10.1007/s10661-012-2527-y | en |
Copyright © DIAS 2013
