Quantifying climatological precipitation and soil moisture as well as interannual variability and trends requires extensive observation. This work focuses on the analysis of available precipitation and soil moisture data and the development of new ways to estimate these quantities. Precipitation and soil moisture characteristics are highly dependent on the spatial and temporal scales. We begin at the point scale, examining hourly precipitation and soil moisture at individual gauges. First, we focus on the Walnut Gulch Experimental Watershed (WGEW), a 150 km² area in southern Arizona. The watershed has been measuring rainfall since 1956 with a very high density network of approximately 0.6 gauges per km². Additionally, there are 19 soil moisture probes at 5 cm depth with data starting in 2002. In order to extend the measurement period, we have developed a water balance model which estimates monsoon season (Jul-Sep) soil moisture using only precipitation for input, and calibrated so that the modeled soil moisture fits best with the soil moisture measured by each of the 19 probes from 2002-2012. This observationally constrained soil moisture is highly correlated with the collocated probes (R=0.88), and extends the measurement period from 10 to 56 years and the number of gauges from 19 to 88. Then, we focus on the spatiotemporal variability within the watershed and the ability to estimate area averaged quantities. Spatially averaged precipitation and observationally constrained soil moisture from the 88 gauges is then used to evaluate various gridded datasets. We find that gauge-based precipitation products perform best followed by reanalyses and then satellite-based products. Coupled Model Intercomparison Project Phase 5 (CMIP5) models perform the worst and overestimate cold season precipitation while offsetting the monsoon peak precipitation forward or backward by a month. Satellite-based soil moisture is the best followed by land data assimilation systems and reanalyses. We show that while WGEW is small compared to the grid size of many of the evaluated products, unlike scaling from point to area, the effect of scaling from smaller to larger area is small. Finally, we focus on global precipitation. Global monthly gauge based precipitation data has become widely available in recent years and is necessary for analyzing the climatological and anomaly precipitation fields as well as for calibrating and evaluating other gridded products such as satellite-based and modeled precipitation. However, frequency and intensity of precipitation are also important in the partitioning of water and energy fluxes. Therefore, because daily and sub-daily observed precipitation is limited to recent years, the number of raining days per month (N) is needed. We show that the only currently available long-term N product, developed by the Climate Research Unit (CRU), is deficient in certain areas, particularly where CRU gauge data is sparse. We then develop a new global 110-year N product, which shows significant improvement over CRU using three regional daily precipitation products with far more gauges than are used in CRU.

The promoters of the large groundwater developments implemented in the 1970's paid little attention to the effects of pumping on soil moisture. A field study, conducted in 1979 in the Tern Area of the Shropshire Groundwater Scheme, revealed that significant quantities of the available moisture could be removed from the root zone of vegetation when drawdown of shallow watertables occurred. Arguments to this effect, supported by the field study evidence, were successfully presented at the Shropshire Groundwater Scheme public inquiry. The aim of this study has been to expand the work which was undertaken in connection with the Shropshire Groundwater Scheme, and to develop a method whereby the effects of groundwater pumping on vegetation can be assessed, and hence the impacts minimised. Two concepts, the critical height and the soil sensitivity depth, formulated during the initial work are at the core of the Environmental Impact Assessment method whose development is described. A programme of laboratory experiments on soil columns is described, as is the derivation of relationships for determining critical heights and field capacity moisture profiles. These relationships are subsequently employed in evaluating the effects of groundwater drawdown. In employing the environmental assessment technique, digitised maps of relevant features of the Tern Area are combined to produce composite maps delineating the extent of the areas which are potentially sensitive to groundwater drawdown. A series of crop yield/moisture loss functions are then employed to estimate the impact of simulated pumping events on the agricultural community of the Tern Area. Finally, guidelines, based on experience gained through evaluation of the Tern Area case study, are presented for use in the design of soil moisture monitoring systems and in the siting of boreholes. In addition recommendations are made for development of the EIA technique, and further research needs are identified.

Typescript. / Digitized by Kansas Correctional Industries

Typescript (photocopy) / xx, 251 leaves, [6] leaves of plates : ill. (part col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Soil Science, 1982

This dissertation focuses on examining the relationship between antecedent soil moisture and summer precipitation in the U.S. Great Plains (GP). The influence of Nino sea surface temperatures (SSTs) on summer precipitation has also been investigated to compare their relative contributions to those from local moisture recycling. Both observational data and model simulations have been used to investigate how and why soil moisture can affect subsequent summer precipitation in the GP. Observational analysis indicates that spring (May 1st) soil moisture is significantly correlated with summer precipitation only during periods when Nino SSTs are not strongly correlated with summer precipitation (e.g. 1925-1936). During periods when Nino SSTs are strongly correlated with summer precipitation (e.g. 1940-1970), spring soil moisture is not a good predictor of summer precipitation in the GP. The periods of strong correlation between Nino SSTs and summer precipitation are associated with strong SST persistence. This study suggests that both local soil moisture and remote SST anomalies (deviation from SST climatology) influence summer precipitation in the GP. The soil moisture anomalies are of greatest importance during years when Nino SST persistence is low. Model results have demonstrated that there are significant differences in precipitation response to soil moisture anomalies depending on their sign (+/-), timing and persistence. The influence of dry soil moisture anomalies on subsequent precipitation tends to last longer than wet soil moisture anomalies when initialized on May 1st. Dry soils can influence summer precipitation in the subsequent 2-3 months. However, the precipitation response to wet soil moisture anomalies is faster and greater in magnitude than the response to dry soil moisture anomalies. Persistent soil moisture anomalies that are sustained for an entire month produced larger precipitation changes than soil moisture anomalies only applied on the first day of the month. It appears that the length of soil moisture memory also depends on the sign of soil moisture anomaly. The results of this study may be model-dependent due to the significant inter-model variations in land surface parameterizations. This may restrict the potential for drawing general conclusions.

Thesis (Ph.D.) -- University of Texas at Arlington, 2009.

Thesis (M.S.)--Ohio State University, 1955. / Includes bibliographical references (leaves 41-42). Available online via OhioLINK's ETD Center

From June to August 2011, Texas experienced the hottest summer ever recorded in the history of the United States, and the state suffered a water shortage that made its vulnerability to drought painfully plain. This disaster sparked new interest in methods of defining drought severity, especially with regard to the variation of soil moisture levels. This thesis assesses the suitability of information from the North American Land Data Assimilation System (NLDAS), an assemblage of land surface models forced with observations data, for quantifying soil moisture levels in Texas. The potential for combining NLDAS data with the Soil Survey Geographic (SSURGO) Database’s available water capacity data is explored. It is discovered that because NLDAS is a hydrological model and SSURGO an agricultural dataset, they employ different definitions of soil moisture storage. Moreover, the temporal variation of soil moisture levels in the SSURGO polygons cannot be inferred from NLDAS data due to the vastly different spatial scales of the two datasets. A relative measure of soil saturation from 0–100% is developed instead and determined to be a more useful indicator of drought than the soil moisture level itself. Calculated solely from NLDAS data, it is used to map the severity of drought in Texas, with the results displayed at the county scale. The temporal variation in soil moisture storage across the state is compared with variations in the gravity anomaly measured by NASA’s Gravity Recovery and Climate Experiment (GRACE) satellites and variations in Texas surface water reservoir levels, both of which are physical measurements of water storage changes. This analysis suggests that the NLDAS data, which is derived from a land surface model, accurately describes subsurface moisture variations. Also, the GRACE gravity anomaly data reveals that during the 2011 drought, the total water storage in Texas was approximately 100 cubic kilometers less than normal. NLDAS data indicates that more than 50% of this deficit was due to losses from the top one meter of the state’s soils. / text

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published_or_final_version / Civil Engineering / Master / Master of Philosophy