Meteorological drought indices are commonly calculated from climatic stations that have long-term historical data and then converted to a regular grid using spatial interpolation methods. The gridded drought indices are mapped to aid decision making by policy makers and the general public. This study analyzes the spatial performance of interpolation methods for meteorological drought indices in the United States based on data from the Co-operative Observer Network (COOP) and United States Historical Climatology Network (USHCN) for different months, climatic regions and years. An error analysis was performed using cross-validation and the results were compared for the 9 climate regions that comprise the United States. Errors are generally higher in regions and months dominated by convective precipitation. Errors are also higher in regions like the western United States that are dominated by mountainous terrain. Higher errors are consistently observed in the southeastern U.S. especially in Florida. Interpolation errors are generally higher in the summer than winter. The accuracy of different drought indices was also compared. The Standardized Precipitation and Evapotranspiration Index (SPEI) tends to have lower errors than Standardized Precipitation Index (SPI) in seasons with significant convective precipitation. This is likely because SPEI uses both precipitation and temperature data in its calculation, whereas SPI is based solely on precipitation. There are also variations in interpolation accuracy based on the network that is used. In general, COOP is more accurate than USHCN because the COOP network has a higher density of stations. USHCN is a subset of the COOP network that is comprised of high quality stations that have a long and complete record. However the difference in accuracy is not as significant as the difference in spatial density between the two networks. For multiscalar SPI, USHCN performs better than COOP because the stations tend to have a longer record. The ordinary kriging method (with optimal function fitting) performed better than Inverse Distance Weighted (IDW) methods (power parameters 2.0 and 2.5) in all cases and therefore it is recommended for interpolating drought indices. However, ordinary kriging only provided a statistically significant improvement in accuracy for the Palmer Drought Severity Index (PDSI) with the COOP network. Therefore it can be concluded that IDW is a reasonable method for interpolating drought indices, but optimal ordinary kriging provides some improvement in accuracy. The most significant factor affecting the spatial accuracy of drought indices is seasonality (precipitation climatology) and this holds true for almost all the regions of U.S. for 1-month SPI and SPEI. The high-quality USHCN network gives better interpolation accuracy with 6-, 9- and 12-month SPI and variation in errors amongst the different SPI time scales is minimal. The difference between networks is also significant for PDSI. Although the absolute magnitude of the differences between interpolation with COOP and USHCN are small, the accuracy of interpolation with COOP is much more spatially variable than with USHCN.

Abstract This thesis describes the development of a new precipitation index-based conceptual water balance model with parameters easily regionalized through the functional relationship with catchment and climate attributes. It also presents a simple method for improving model dynamics for streamflow simulations in a non-stationary climate. The model was developed for streamflow modelling and prediction in high-latitude catchments, where model parameter regionalization is difficult due to limited availability of hydrological data for the region. The model couples a snow accumulation and melt formulation with a current precipitation index (CPI) formulation to simulate daily precipitation in runoff hydrograph pattern from catchments with seasonal snow cover. Using new runoff conversion factors CT and Lf, and a threshold flow factor ThQ, the simulated CPI hydrograph is converted into daily runoff and routed using the transformation function Maxbas. The model was developed in Microsoft Excel workbook and tested in 32 catchments in Finland, a region with considerable seasonal snow cover. The results showed that the model can adequately simulate and reproduce the dynamics of daily runoff from catchments where the underlying physical conditions are not known. In addition, incorporating temperature conditions influencing inter-annual variability in streamflow into the model structure improved its structural dynamics, thereby improving its performance in a non-stationary climate. Most model parameters showed strong relationships with observable catchment characteristics, climate characteristics, or both. The parameter functional relationships derived from the model parameter-catchment relationships produced equally good model results when applied to independent test catchments used as mock-ungauged catchments. Inclusion of snow-water equivalent records and use of multiple objective functions for snow-water equivalent and runoff simulations during model optimization helped reduce the effect of parameter equifinality, making it easier to determine optimal parameter values. The current precipitation index (CPIsnow) model is a parsimonious tool for predicting streamflow in data-limited high-latitude regions. / Tiivistelmä Tämä väitöskirja käsittelee yksinkertaisen sadantaan perustuvan konseptuaalisen vesitasemallin kehitystä ja soveltamista boreaalisille valuma-alueille sekä malliin liittyvää alueellista parametrisointia valuma-alueominaisuuksien ja ilmastoaineiston perusteella. Hydrologinen malli on luotu laskemaan ja ennustamaan valuntaa pohjoisille valuma-alueille, joilta on vähän hydrologista tietoa. Malli yhdistää lumen kertymisen ja sulannan tunnettuun sadantaindeksiin perustuvaan malliin (CPI) ja edelleen simuloi päivittäisen hydrografin valuma-alueille, joilla on selkeä lumipeitteinen ajanjakso. Malli laskee MaxBas funktion avulla CPI:llä muodostetun hydrografin päivittäiseksi valunnaksi valuntaan liittyvien malliparametrien CT ja Lf sekä virtaaman kynnysarvon ThQ avulla. Malli kehitettiin Excel-ympäristössä ja sitä testattiin 32 valuma-alueella Suomessa. Valuma-alueet edustivat maantieteellisesti kattavasti alueita, joilla esiintyy tyypillisesti kausittainen lumipeite. Saadut tulokset osoittivat, että kehitetty malli simuloi ja tuottaa päivittäisen valunnan riittävällä tarkkuudella valuma-alueille, vaikka hydrologista ja fysikaalista tietoa alueilta olisi niukasti. Useimmat malliparametrit olivat vahvasti riippuvaisia joko valuma-alue ominaisuuksista tai ilmastollisista parametreista tai molemmista. Parametrien funktionaalinen yhteys muodostettiin valuma-alueiden ominaisuuksien perusteella ja testattiin riippumattomalla valuma-aluejoukolla hyvin tuloksin. Malliparametrien samatavoitteellisuutta eli ekvifinaliteettiä voitiin vähentää huomioimalla mallissa lumen vesiarvomittaukset sekä hyödyntämällä useita parametrisia funktioita. Tällöin myös optimaalisten parametrien löytyminen nopeutui ja helpottui. Tämän väitöstyön pohjalta syntynyt uusi sadannan indeksiin pohjautuva laskentamalli (CPIsnow) mahdollistaa valunnan arvioinnin pieniltä valuma-alueilta, joilta on niukasti aineistoa saatavilla ja joissa lumen sulanta ja kertyminen ovat keskeisiä hydrologisia prosesseja.

Anthropogenic activities including urbanization, rapid industrialization, deforestation and burning of fossil fuels are broadly agreed on as primary causes for ongoing climate change. Scientists agree that climate change over the next century will continue to impact water resources with serious implications including storm surge flooding and a sea level rise projected for North America. To date, the majority of climate change studies conducted across the globe have been for large-sized watersheds; more attention is required to assess the impact of climate change on smaller watersheds, which can help to better frame sustainable water management strategies. In the first of three studies described in this dissertation, trends in annual precipitation and air-temperature across the Commonwealth of Kentucky were evaluated using the non-parametric Mann-Kendall test considering meteorological time series data from 84 weather stations. Results indicated that while annual precipitation and mean annual temperature have been stable for most of Kentucky over the period 1950-2010, there is evidence of increases (averages of 4.1 mm/year increase in annual precipitation and 0.01 °C/year in mean annual temperature) along the borders of the Kentucky. Considered in its totality, available information indicates that climate change will occur – indeed, it is occurring – and while much of the state might not clearly indicate it at present, Kentucky will almost certainly not be exempt from its effects. Spatial analysis of the trend results indicated that eastern part of the state, which is characterized by relatively high elevations, has been experiencing decreasing trends in precipitation. In the second study, trends and variability of seven extreme precipitation indices (total precipitation on wet days, PRCPTOT; maximum length of dry and wet periods, CDD and CWD, respectively; number of days with precipitation depth ≥20 mm, R20mm; maximum five-day precipitation depth, RX5day; simple daily precipitation intensity, SDII; and standardized precipitation index, SPI were analyzed for the Kentucky River Basin for both baseline period of 1986-2015 and the late-century time frame of 2070-2099. For the baseline period, the majority of the indices demonstrated increasing trends; however, statistically significant trends were found for only ~11% of station-index combinations of the 16 weather stations considered. Projected magnitudes for PRCPTOT, CDD, CWD, RX5day and SPI, indices associated with the macroweather regime, demonstrated general consistency with trends previously identified and indicated modest increases in PRCPTOT and CWD, slight decreases in CDD, mixed results for RX5day, and increased non-drought years in the late century relative to the baseline period. The study’s findings indicate that future conditions might be characterized by more rainy days but fewer large rainfall events; this might lead to a scenario of increased average annual rainfall but, at the same time, increased water scarcity during times of maximum demand. In the third and final study, the potential impact of climate change on hydrologic processes and droughts over the Kentucky River basin was studied using the watershed model Soil and Water Assessment Tool (SWAT). The SWAT model was successfully calibrated and validated and then forced with forecasted precipitation and temperature outputs from a suite of CMIP5 global climate model (GCMs) corresponding to two different representative concentration pathways (RCP 4.5 and 8.5) for two time periods: 2036-2065 and 2070-2099, referred to as mid-century and late-century, respectively. Climate projections indicate that there will be modest increases in average annual precipitation and temperature in the future compared to the baseline (1976-2005) period. Monthly variations of water yield and surface runoff demonstrated an increasing trend in spring and autumn, while winter months are projected as having decreasing trends. In general, maximum drought length is expected to increase, while drought intensity might decrease under future climatic conditions. Hydrological droughts (reflective of water availability), however, are predicted to be less intense but more persistent than meteorological droughts (which are more reflective of only meteorological variables). Results of this study could be helpful for preparing any climate change adaptation plan to ensure sustainable water resources in the Kentucky River Basin.

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