Document Type

Thesis - Open Access

Award Date


Degree Name

Master of Science (MS)



First Advisor

Jerald Tunheim


Because of their repetitive flight patterns and broad spatial coverage, satellites hold great promise for supplying the data necessary to predict soil moisture conditions. Already satellite data have been used to predict such input parameters to soil moisture models as solar radiation values and leaf area indices. In addition, surface soil moisture or rainfall events could be detected remotely and used as model inputs. Conceivably, satellite imagery could be used to. predict most, if not all, of the inputs into a soil moisture model. Although the use of satellite data sounds like a timely panacea, there are some inherent questions to be answered first. Of importance is the question of whether existing soil moisture models (which heretofore have been used locally) can be applied or adjusted to regional use. Hence, this study was initiated with the purpose of determining if current soil moisture theory can be adjusted to large area use. Since there are many different approaches to predicting soil moisture, this study was limited to the water balance approach. In this method, total soil moisture is the difference between the total water into the system (precipitation or irrigation) and the total water out of the system. The outgoing water can be in the form of transpiration through the plant canopy or evaporation from the soil surface. Evapotranspiration equations attempt to model these two processes simultaneously as one water loss value. This combined process, referred to as evapotranspiration, is dependent upon climatic variables, such as solar radiation, air temperature; and vegetative variables, such as canopy type and leaf area index. Therefore, empirical crop derived from field data to adjust the by using the water balance approach, the k-values used to calculate an actual evapotranspiration rate must be derived for large spatial areas before soil moisture prediction over these broad areas is possible. Furthermore, the effects of diverse differences these crop parameters understood in soil type, soil moisture contents, and crop variety on coefficients need to be studied. In other words, the controlling or affecting the coefficients need to be before large scale prediction of evapotranspiration and subsequently soil moisture is an attempt to understand the crop coefficients and their adjustment to large areas, this study was designed with the following objectives: 1. Derive crop coefficients from actual soil moisture data to adjust potential evapotranspiration rates to actual evapotranspiration rates over a broad spatial region (state of South Dakota). 2. Determine what measurable variables significantly affect the crop coefficients. 3. Determine an equation to predict crop coefficients from measurable parameters such that spatial and temporal effects are negligible (i.e. adjust the coefficients for broad area, year after year use).

Library of Congress Subject Headings

Crops and climate
Soil moisture -- South Dakota -- Remote sensing



Number of Pages



South Dakota State University