Alan Mair

Comparison of Rainfall Interpolation Methods in a Mountainous Region of a Tropical Island

A total of 21 gauges across the mountainous leeward portion of the island of Oʻahu, Hawaiʻi, were used to compare rainfall interpolation methods and assess rainfall spatial variability over a 34-month monitoring period from 2005 to 2008. Traditional and geo- statistical interpolation methods, including Thiessen polygon, inverse distance weighting (IDW), linear regression, ordinary kriging (OK), and simple kriging with varying local means (SKlm), were used to estimate wet and dry season rainfall. The linear regression and SKlm methods were used to incorporate two types of exhaustive secondary information: (1) elevation extracted from a digital elevation model (DEM), and (2) distance to a regional rainfall maximum. The Thiessen method produced the highest error, whereas OK produced the lowest error in all but one period. The OK method produced more accurate predictions than linear regression of rainfall against elevation when the correlation between rainfall and elevation is moderate (R < 0:82). The SKlm method produced lower error than linear regression and IDW methods in all periods. Comparison of the OK interpolation map with gridded isohyet data indicate that the areas of greatest rainfall deficit were confined to the mountainous region of west Oʻahu. DOI: 10.1061/(ASCE)HE.1943-5584.0000330.

Logistic regression modeling to assess groundwater vulnerability to contamination in Hawaii, USA

Capture zone analysis combined with a subjective susceptibility index is currently used in Hawaii to assess vulnerability to contamination of drinking water sources derived from groundwater. In this study, we developed an alternative objective approach that combines well capture zones with multiple-variable logistic regression (LR) modeling and applied it to the highly-utilized Pearl Harbor and Honolulu aquifers on the island of Oahu, Hawaii. Input for the LR models utilized explanatory variables based on hydrogeology, land use, and well geometry/location. A suite of 11 target contaminants detected in the region, including elevated nitrate (>1 mg/L), four chlorinated solvents, four agricultural fumigants, and two pesticides, was used to develop the models. We then tested the ability of the new approach to accurately separate groups of wells with low and high vulnerability, and the suitability of nitrate as an indicator of other types of contamination. Our results produced contaminant-specific LR models that accurately identified groups of wells with the lowest/highest reported detections and the lowest/highest nitrate concentrations. Current and former agricultural land uses were identified as significant explanatory variables for eight of the 11 target contaminants, while elevated nitrate was a significant variable for five contaminants. The utility of the combined approach is contingent on the availability of hydrologic and chemical monitoring data for calibrating groundwater and LR models. Application of the approach using a reference site with sufficient data could help identify key variables in areas with similar hydrogeology and land use but limited data. In addition, elevated nitrate may also be a suitable indicator of groundwater contamination in areas with limited data. The objective LR modeling approach developed in this study is flexible enough to address a wide range of contaminants and represents a suitable addition to the current subjective approach.

Assessing Rainfall Data Homogeneity and Estimating Missing Records in Mākaha Valley, O‘ahu, Hawai‘i

The objectives of this study were to examine records from long-term rain gauges in Mākaha Valley for data homogeneity and to compare methods of estimating missing data. Double mass analysis was used to investigate data homogeneity. Results show that tree growth near one gauge has reduced rainfall catch by 21–25% since 1974. Four methods for estimating missing daily rainfall data were then tested using index gauges selected from a network of 21 active rain gauges. The number of index gauges and their order of selection were varied according to proximity and correlation. Selection by correlation significantly improved the performance of the station average and inverse distance methods for most cases, as well as the normal ratio method for the case when only one gauge is used. The normal ratio method produces the lowest error when two to five index gauges are used; the inverse distance method yields the lowest error when six or seven index gauges are used. Direct substitution produces better accuracy than th...

Improved Calibration Functions of Three Capacitance Probes for the Measurement of Soil Moisture in Tropical Soils

Single capacitance sensors are sensitive to soil property variability. The objectives of this study were to: (i) establish site-specific laboratory calibration equations of three single capacitance sensors (EC-20, EC-10, and ML2x) for tropical soils, and (ii) evaluate the accuracy and precision of these sensors. Intact soil cores and bulk samples, collected from the top 20 and 80 cm soil depths at five locations across the Upper Mākaha Valley watershed, were analyzed to determine their soil bulk density (ρb), total porosity (θt), particle size distribution, and electrical conductivity (EC). Laboratory calibration equations were established using soil packed columns at six water content levels (0–0.5 cm3 cm−3). Soil bulk density and θt significantly varied with sampling depths; whereas, soil clay content (CC) and EC varied with sampling locations. Variations of ρb and θt at the two depths significantly affected the EC-20 and ML2x laboratory calibration functions; however, there was no effect of these properties on calibration equation functions of EC-10. There was no significant effect of sampling locations on the laboratory calibration functions suggesting watershed-specific equations for EC-20 and ML2x for the two depths; a single watershed-specific equation was needed for EC-10 for both sampling depths. The laboratory calibration equations for all sensors were more accurate than the corresponding default equations. ML2x exhibited better precision than EC-10, followed by EC-20. We conclude that the laboratory calibration equations can mitigate the effects of varying soil properties and improve the sensors’ accuracy for water content measurements.

Temporal and spatial variability of rainfall and climate trend on Jeju Island

The temporal and spatial analyses of rainfall and temperature were conducted for understanding spatial variability and climate trend on Jeju Island. Rainfall data from 1992 to 2009 were used for the spatial analyses, and missing data were adjusted on Mt. Halla and along the northeast coast to reduce uncertainty of spatial variability. In addition, rainfall time series data of both Jeju City and Seogwipo City from 1961 to 2009 were analyzed for a long-term trend and identification of droughts. Mean annual rainfall for the period 1992–2009 shows an area of maximum rainfall centered around Mt. Halla where maximum annual rainfall reaches more than 4,300 mm and mean island rainfall is 2,082 mm. Upward trends in rainfall intensity, magnitude, and dryness conditions at the Jeju City and Seogwipo City from 1961 to 2009 suggest that rainfall has intensified with greater quantities of rainfall occurring over shorter durations, with longer dry periods between storm events. The annual cycle shows a distinct monsoon signature with peak rainfall typically occurring in August. Rainfall seasonality shows a shift in peak rainfall from June, July, and August, to July, August, and September. The most severe droughts in the period 1961–2009 were identified using a 12-month composite SPI. Three severe droughts each lasting around two years were identified over a relatively short nine-year period from 1964–1972.

Simple equations for temperature simulations on mid-latitude volcanic islands: a case study from Jeju (Republic of Korea)

Volcanic islands can be characterized by remarkable surface air temperature variability. The distribution of weather stations in these settings, however, is typically too sparse to reliably describe temperature patterns which can complicate regional-scale hydrologic analyses. Here, a simple method is presented to estimate near surface air temperatures for such a setting (Jeju Island, Republic of Korea). The method utilizes temperature lapse rates (TLR; the change in temperature with elevation) which are computed for Tmin, Tave, and Tmax for two distinct hemispheres: the more arid northern flanks and the more humid southern flanks of the central orographic divide. Computed TLRs vary greatly with season and location relative to the orographic divide and, unlike in continental mountainous settings, are generally highest for Tmin in winter. Cross-validation results indicate a good match between modeled and measured values particularly for high altitude stations that are characterized by highest precipitation rates. Because temporally changing TLRs perform better than the often applied theoretical constant environmental lapse rate of 6.5 °C/km, monthly mean TLRs compiled from temperature data from Jeju Island are presented here as proxies for surface air temperature simulation efforts in similar settings for which only limited climatic data are available.