A GIS FOR THE MANAGEMENT OF AGRICULTURAL WATER RESOURCES IN THE BOULDER COUNTY, COLORADO PARKS AND OPEN SPACE PROGRAM

Transcription

1 A GIS FOR THE MANAGEMENT OF AGRICULTURAL WATER RESOURCES IN THE BOULDER COUNTY, COLORADO PARKS AND OPEN SPACE PROGRAM Submitted by Kristina L. VanDenBosch Department of Forest, Rangeland and Watershed Stewardship In partial fulfillment of the requirements For the Degree of Master of Science Colorado State University Fort Collins, Colorado Fall 2008

2 COLORADO STATE UNIVERSITY April 14, 2008 WE HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER OUR SUPERVISION BY KRISTINA L. VANDENBOSCH ENTITLED A GIS FOR THE MANAGEMENT OF AGRICULTURAL WATER RESOURCES IN THE BOULDER COUNTY, COLORADO PARKS AND OPEN SPACE PROGRAM BE ACCEPTED AS FULFILLING IN PART REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE. Committee on Graduate Work Steven Fassnacht Reagan Waskom Advisor Melinda Laituri Department Head Mike Manfredo ii

3 ABSTRACT OF THESIS A GIS FOR THE MANAGEMENT OF AGRICULTURAL WATER RESOURCES IN THE BOULDER COUNTY, COLORADO PARKS AND OPEN SPACE PROGRAM Boulder County, Colorado owns and manages 57,727 acres of land directly and 36,249 acres of conservations easements on privately owned land. The County also owns a substantial amount of water resources, with a value in excess of $60 million, primarily used for agricultural production. All of these resources are managed by the Boulder County Parks and Open Space (BCPOS) department. As the demand for water along the Front Range of Colorado increases, BCPOS must find ways to maximize the management of its water resource portfolio to support long term, sustainable agriculture within the open space program. Using a Geographic Information System (GIS) to explore and analyze the spatial distribution and relationships between and among agricultural and water information enables BCPOS to make informed decisions about agricultural water management. This study develops and evaluates an integrated GIS for water management for agricultural properties in the open space program. This agricultural water management system incorporates spatial and non-spatial data from a variety of iii

4 sources, formats, and models. Data are imported into ESRI s ArcGIS 9.2 where spatial relationships are analyzed and evaluated. Multiple spatial scales are addressed, ranging from the agricultural field to the County. The GIS calculates and ranks the surplus and deficit of irrigation water, the on farm and off farm irrigation efficiencies, and the overall agricultural irrigation efficiency. The data results are output in graphic and tabular formats for use in the agricultural water management decision making process. The GIS is tested in a pilot project on Boulder County holdings in the Highland Study Area of Boulder County. The study area is comprised of 14 farms spread over 16,000 acres over northeastern Boulder County. The study area includes 1,522 acres of irrigated cropland and 1,796 acre-feet of irrigation water owned and managed by Boulder County Parks and Open Space. Results revealed that 71% of the 14 properties in the Highland Study were water short by 100 acre-feet or more for the crops grown in One property, Strawberry Holdings, had a water surplus of acre-feet. The Harless property and the Rocky Mountain Fuel 2 property were found to have the highest irrigation efficiencies, but also had the largest water deficits, and acre-feet, respectively. Results also showed that installing center pivot sprinklers, without also increasing the water supply, would not be sufficient to meet the irrigation water requirements. This study illustrates how the GIS can be a successful and effective water resource management tool for agricultural water resources in the open space program at Boulder County. The GIS allows managers to explore the iv

5 relationships between data and run scenarios that would otherwise be too complicated and too time consuming to process manually. Kristina L. VanDenBosch Department of Forest, Rangeland and Watershed Stewardship Colorado State University Fort Collins, Colorado Fall 2008 v

6 ACKNOWLEDGEMENTS I would like to express my appreciation for my advisor, Dr. Melinda Laituri, for her support and guidance throughout this process. She has been invaluable in providing technical advice and keeping me from straying off on too many tangents. I thank my committee members, Dr. Steven Fassnacht and Dr. Reagan Waskom. Steven provided great assistance in providing prospective and big picture thinking. Reagan was critical in providing extensive agricultural support and expertise. I owe a great deal of gratitude to Boulder County Parks and Open Space. My colleagues provided me with the ability to attend graduate school and the support to develop this project. I would like to especially thank Rob Alexander for providing the impetus and long-term support for this project, as well as his professional expertise and insights during this process. I thank Meredith Dutlinger and John Staight for providing technical assistance, for emotional support, and for picking up the slack. I also would like to express my appreciation to Sasha Charney, Rich Koopmann, Carrie Inoshita and Larissa Read for their professional assistance and emotional support. Finally, thank you to all of my friends and family who bore with me through this long and demanding journey. Especially to my husband, John, who always supported me and believed in me. vi

7 TABLE OF CONTENTS Chapter 1. Introduction Introduction Research Purpose and Objectives Structure and Organization Chapter 2. Literature Review GIS in Agricultural Irrigation Management Irrigation Efficiency Ditch Surface Efficiency Irrigation Application Method Efficiency Irrigation Management Capability Irrigation Requirement Estimating Consumptive Use Summary Chapter 3. A GIS for the Management of Agricultural Water Resources in the Boulder, County Parks and Open Space Program Abstract Introduction System Data Application Highland Case Study Discussion Future Research Conclusions Literature Cited Chapter 4. Lessons Learned Literature Cited Appendices vii

8 LIST OF FIGURES Figure 3.1 Relationships of spatial units of agricultural water management components and their relationships in the Boulder County GIS Figure 3.2 General framework of the integrated GIS for managing agricultural water in the open space program at Boulder County Figure 3.3 Various methods of linking spatial and tabular data in the Boulder County GIS using the ditch, the ditch diversion points, the ditch service areas, and the open space properties Figure 3.4 Procedure for ranking total agricultural water efficiency in the Boulder County GIS Figure 3.5 Boulder County, Colorado, USA Figure 3.6 Water delivery system and watersheds in Boulder County, Colorado 55 Figure 3.7 Land owned or managed by Boulder County Parks and Open Space and other publicly owned lands in Boulder County Figure 3.8 Highland Study Area, Boulder County Figure 3.9 Scenario 1 irrigation system efficiency rankings Figure 3.10 Scenario 1 irrigation water allocation surplus and deficit ranking Figure3.11 Scenario 1 total agricultural water use efficiency ranking Figure 3.12 Scenario 2 irrigation water allocation surplus and deficit ranking Figure 3.13 Scenario 2 total agricultural water use efficiency ranking Figure 3.14 Scenario 3 total agricultural water use efficiency ranking Figure3.15 Physical condition of ditches in the Highland Study Area Figure 3.16 Field level irrigation delivery system conditions calculated by averaging the conditions of all structures that serve each field viii

9 LIST OF TABLES Table 2.1 Agricultural irrigation system descriptions and efficiency definitions. 18 Table 2.2 Factors effecting water loss in the components of an irrigation delivery system Table 2.3 Field irrigation application system efficiency values Table 3.1 Size ranges of spatial units in the Boulder County GIS, in acres Table 3.2 Spatial and non-spatial data descriptions, sources, accuracy, and formats in the Boulder County GIS Table 3.3 Protected Public Lands in Boulder County Table 3.4 Properties included in the Highland Study Area and their characteristics Table 3.5 Descriptions of the scenarios run in the pilot project in the Highland Study Area Table 3.6 Scenario 1 Results Summary Table 3.7 Comparison of irrigation water surplus and deficit values between scenarios 1, 2, and ix

10 ACRONYMS AEGIS-WIN AF AFSIRS ASCE BPCOS CBT CIG CRDSS CROPWAT EP ESRI ET FAO FSA GIS GPS IWM IWR NCWCD NDVI NRCS POSAG POS Tracker SCS SSURGO StateCU SWAP SWAT TR-21 USDA Agricultural and Environmental Geographic Information System Acre-feet Agricultural Field Scale Irrigation Requirements Model American Society of Civil Engineers Boulder County Parks and Open Space Colorado Big Thompson Project Colorado Irrigation Guide Colorado River Decision Support System Decision support system for planning and management of irrigation Effective Precipitation Environmental System Research Institute Evapotranspiration Food and Agriculture Organization Farm Services Agency Geographic Information System Global Positioning System Irrigation Water Management Irrigation Water Requirement Model Northern Colorado Water Conservancy District Normalized Difference Vegetation Index Natural Resources Conservation Service Parks and Open Space Agricultural Database Parks and Open Space Property and Water Database Soil Conservation Service Soil Survey Geographic State Consumptive Use Model Soil-Water-Atmosphere-Plant Soil and Water Assessment Tool SCS Blaney-Criddle Consumptive Use Equation United States Department of Agriculture x

11 1. Chapter 1. Introduction 1.1. Introduction Boulder County, Colorado protects over 90,000 acres of public land and a water portfolio with in a value in excess of $60 million (Boulder County Parks and Open Space, 2008). The residents of Boulder County have charged the Parks and Open Space Department with the responsibility of managing these resources for multiple uses, including preserving the agricultural heritage of the County by creating a sustainable local agricultural program. The majority of the County s water portfolio is used to support this agricultural program. The agricultural program operates by leasing the agricultural lands and water to local, private farmers. These farmers, within the framework defined by Boulder County, make production decisions: which crops to produce, which products to apply, and when and how much to irrigate. The County s responsibility is to provide sufficient resources to allow farmers to maximize their production and to offer technical assistance, guidance, and oversight. Making decisions about the management of water resources for agricultural production requires a thorough understanding of complex information including climatic conditions, natural and artificial water systems, agricultural practices, and legal conditions. All of these pieces of information have a geographic distribution which makes them ideally suited to be incorporated into a Geographic 11

12 Information System (GIS). Using a GIS, Boulder County can integrate these various data sources and types and explore spatial relationships. With a better understanding of the spatial distribution and relationships of the agricultural and water resources, better decisions can be made by Boulder County. For example, knowing where water supply is insufficient for production can help staff to make decisions about which water to add to the water portfolio or where to focus irrigation conservation methods. This information can also help clarify agricultural water resources decision intricacies to non-expert decision makers by clearly laying out methodologies and representing results in a graphic format Research Purpose and Objectives The purpose of this research was to develop an integrated GIS for the management of agricultural water resources on agricultural lands owned and managed by Boulder County. This GIS was tested on the Highland Study Area to determine agricultural water efficiencies. Objectives for the GIS include: To link disparate datasets and formats together; To assess irrigation water requirement and supply for agricultural open space properties in the Highland Study Area; To determine agricultural water efficiencies for agricultural open space properties in the Highland Study Area; To integrate requirement, supply and efficiency values to calculate an agricultural water efficiency ranking in the GIS. 12

13 This study is relevant and valuable due to the unique nature of the Boulder County Parks and Open Space program. Very few local open space programs have a program that manages and supports such large acreages of local agricultural production and such a large amount of water resources used to support that agricultural production. The City of Boulder (City of Boulder, 2008) and Larimer County open space programs (Larimer County, 2008) are similar to Boulder County s open space program, but are smaller in scale and do not have formalized spatial analysis capabilities, such as presented in this study Structure and Organization This thesis is organized into 4 main chapters. Chapter 1 lays out the research purpose, objectives and structure. To provide background on the research, Chapter 2 reviews related literature. Topics covered in the literature review include the use of GIS in agricultural water management, irrigation efficiencies, irrigation water requirements and the method of estimating crop consumptive use. Chapter 3 was written as a journal article and will be submitted to the Journal of Water Resources Management and Planning. This chapter presents the conceptual development and implementation of the GIS and datasets used in the study. Results and conclusions of the study are also discussed. Chapter 4 presents conclusions drawn through the course of the study and lessons learned throughout the research process. Appendix 1 details the metadata for the geographic datasets. Appendix 2 presents the technical process of the GIS implementation. Appendix 3 details the procedure used to rate the physical condition of ditches and diversion structures. Appendix 4 describes the equations 13

14 used in the GIS model. Appendix 5 lists the water supply companies and water rights in which Boulder County has ownership interest. Appendix 6 includes data used to evaluate Scenario 1. 14

15 2. Chapter 2. Literature Review For management purposes, Boulder County has defined efficient agricultural water use as both minimizing water loss from the irrigation delivery system and having the appropriate amount of water necessary for optimal agricultural production. This chapter provides the scientific foundation for determining agricultural water efficiencies using GIS. First, the use of GIS in managing agricultural irrigation water is discussed. The second section details the concept of irrigation efficiency and discusses factors used to evaluate efficiency values. Following this is a discussion of irrigation water requirements and factors used to determine this requirement. Finally, various methods and models for estimating crop consumptive use are reviewed GIS in Agricultural Irrigation Management Effectively and efficiently managing agricultural water requires a comprehensive understanding of all of the factors, including soils, hydrology, infrastructure, crops, and climate. (Tdorovic and Steduto, 2003). GIS allows spatial and temporal variations to be accounted for in these data, instead of assuming homogeneity. Integrating GIS and agricultural water management allows interactions and relationships between the variables to be explored, analyzed and displayed for multiple purposes. 15

16 Tsanis and Naoum (2003) used spatially distributed meteorological and crop data to estimate crop evapotranspiration (ET) for the island of Crete. The crop evapotranspiration calculations were integrated within the GIS. Integrating the calculations within a GIS enabled the researchers to take advantage of GIS capabilities, such as linear interpolation for estimating crop ET. Santhi et al. (2005) used GIS to assess water supply and demand at a regional level in Lower Rio Grande Valley in Texas, using high spatial and temporal resolution data and models. Researchers found that the system was capable of accurately simulating both agricultural and hydrological management process, as well as being able to represent the spatial and temporal variations inherent in a large irrigation system (Santhi et al., 2005). The system was also found to be useful in addressing future scenarios. Many studies have integrated existing hydrologic or agronomic models into a GIS (Khan and Abbas, 2007; Santhi et al., 2005; Satti et al,. 2004; Heinemann et al., 2002). There are many advantages to using existing models, which are readily available, well tested, and widely accepted. Interfacing them with a GIS extends the scope of application by expanding their use beyond a specific site location (Hartkamp, 1999). It also enables decision makers to examine management alternatives and their impacts. Satti (2004) created an integrated system to permit and plan for irrigation water at the field level. GIS was integrated with a field scale irrigation management model, Agricultural Field Scale Irrigation Requirements Simulation (AFSIRS), in order to create a distributed, regional, crop drought water 16

17 requirement model that captures the wide variety of crops in the region, the heterogeneous soil types, and the spatially variable climate data (Satti et al., 2004). A number of studies have incorporated remote sensing with a GIS for irrigation water management (de Santa Olalla et al., 2003; Ray and Dadhwal, 2001). Remote sensing is used to identify crop types, based on phenological evolution, using a vegetative index, such as the normalized difference vegetation index (NDVI). These data are input into a GIS which calculates the irrigation requirement, based on crop type Irrigation Efficiency Irrigation efficiency is defined by the USDA as an index used to quantify the beneficial use of water diverted for irrigation purposes (U.S. Department of Agriculture, 2007b). Bos and Nugteren (1990) divided the evaluation of the irrigation efficiency of the irrigation system into three components: the conveyance system, the distribution system and the field application (Table 2.1). The GIS calculates the irrigation efficiency for each component of the irrigation system using the factors identified in this section. These values are applied to the property to compare the spatial distribution of irrigation efficiencies in the study area. 17

18 Table 2.1 Agricultural irrigation system descriptions and efficiency definitions (Source: 1 U. S. Department of the Interior 1979, 2 Howell 2003, 3 Rao 1993) System Description Efficiency Conveyance The infrastructure that moves the water from its source through the main and lateral ditches to the farm1 The difference in the amount of water that is released into an irrigation system and the amount of that water which is delivered 2 Distribution Application The infrastructure that conveys the water from the conveyance system to the individual fields is considered the water distribution system1 The method in which the water is moved from the field inlet to the crop1 The difference in the amount of water which is delivered to the distribution system, via the conveyance system, and the amount of water available at the field inlet3 The amount of water stored in the crop root zone and accessible to the crop versus the amount of water applied during irrigation 2 Water loss in an irrigation system falls into three general categories: physical factors, management factors, and institutional and social factors (U.S. Department of the Interior, 1979). The variables defining each of these categories differ between the conveyance, distribution and application components of the system, therefore each must be evaluated independently (Table 2.2). 18

19 Table 2.2 Factors effecting water loss in the components of an irrigation delivery system (Source: U. S. Department of the Interior 1979) System Physical Management Institutional & Social Conveyance Loss Managment Ability Water law & court decrees Condition Water prices Vegetation Environmental conflicts Financial capabilities Social attitudes Distribution Surface efficiency Farmer Capability Water law & court decrees Measurement structures Water prices Farm layout Environmental conflicts Maintenance Financial capabilities Social attitudes Application Irrigation method Farmer Capability Water law & court decrees Soil type Water prices Slope Environmental conflicts Financial capabilities Social attitudes 2.3. Ditch Surface Efficiency Ditch surfaces can be of three types: unlined, lined or piped. Unlined ditches are the least efficient ditch delivery system due to loss through the soil surface. Earthen surface ditches can have water loss ranging from 20 50%; yet well designed and maintained ditches have the potential to be as efficient as ditches with concrete lining (Hill, 2002). Water loss is highly affected by the permeability of the soil in the ditch. A soil with high clay content will have significantly lower seepage loss relative to a sandy or gravelly soil (U.S. Department of Agriculture, 2007b). Ditches lined with an impermeable membrane decrease the amount of water lost through seepage, compared to unlined ditches. Ditches lined with concrete and a buried membrane can reduce seepage losses by up to 95% (Barta, 2004). Water loss in unlined ditches can still occur through surface evaporation or through seepage, if the structure is not well maintained. Piped ditches, both buried and exposed, are the most efficient 19

20 delivery system, as they eliminate water loss due to both seepage and evaporation (Barta, 2004). Loss can still occur around diversion structures, headgates, valves and joints if the system is in poor condition Irrigation Application Method Efficiency Irrigation application systems are generally classified into three types: surface, sprinkler, and micro-irrigation (Barta et al., 2004). Walker (1989) defined surface irrigation systems as systems in which the water flows by gravity and the method of conveyance across the field is the actual field surface. These can be further defined by the particular method in which the water is conveyed across the field surface: basin irrigation, border irrigation, furrow irrigation, and uncontrolled flooding. Sprinkler systems are generally defined by their physical structure and method of movement. These fall into three broad categories: handmove laterals, side roll systems, and center pivot systems (Barta, 2004). A microirrigation system is an irrigation system which carries water directly to the target plant in a slow, controlled manner. These can be further categorized in the following categories: surface drip, subsurface drip and microsprinklers (Barta, 2004). The range of irrigation efficiency values for each system applicable in Boulder County and their averages are given in Table

21 Table 2.3 Field irrigation application system efficiency values (Source: Howell 2003) IrrigationMethod ValueRange Average Ranking Microirrigation Subsurface Drip Surface Drip Microsprinklers Sprinkler Impact Sprinkler Spray Nozzle Side Roll Sprinkler Surface Level Furrow Graded Furrow w/tailwater Reuse Graded Furrow Graded Border Howell 2003 Irrigation systems, even surface systems, have the potential to be very efficient. Table 2.3 indicates that even graded border or graded furrow systems can reach 80% efficiency. Realistically, irrigation systems seldom reach the full efficiency potential. Generally, the upper ends of the efficiency range will only be reached when there is sufficient incentive to be efficient, for example under water shortages or economic pressure, or when the farmer has sufficient experience and training with a particular irrigation system to operate it properly (Tanji, 1994; Northern Colorado Water Conservancy District, 1992). Therefore, the lower ends of the ranges are more realistic efficiency expectations and were used in this study Irrigation Management Capability Traditionally, land, labor and capital have been considered the three primary factors of farm production. Management is considered to be a fourth factor necessary to the success of an agricultural operation (Kay and Edwards, 1999). Farmer management capacity has a significant effect on the productive potential 21

22 of one farm relative to another, even when the environmental and economic conditions are relatively equal. Ruogoor et al. (1998) define management capacity as having the appropriate personal characteristics and skills to deal with the right problems and opportunities in the right moment in the right way. One way to study and evaluate the management ability of a farmer is by examining the explicit and measurable actions which are related to the decision making process (Ruogoor et al., 1998). Irrigation management requires farmers to have the knowledge and skills to make appropriate decisions regarding when to irrigate, how much to irrigate, and to correctly operate and maintain the irrigation system (Hoffman, 1990). Measurable and observable actions can be identified to evaluate a farmer s ability to make these irrigation decisions. These include: Maintaining good irrigation records Participating in NRCS Irrigation Water Management (IWM) planning Working with crop or irrigation consultants Maintaining equipment in good condition Maintaining irrigation system in good condition Using ET or soil moisture methods to monitor the irrigation requirement Minimizing tail water runoff 22

23 2.6. Irrigation Requirement The irrigation requirement for a given crop is the amount of water necessary for crop ET, soil leaching, and other miscellaneous water needs that are not met by rainfall or water stored in the soil (U. S. Department of Agriculture, 1988; Smajstrla and Zazueta, 2002). The irrigation requirement is used in the GIS to determine the water demand for each agricultural field, which is then aggregated to determine the irrigation water demand for the property Evapotranspiration Evapotranspiration is the sum of water consumed through the evaporation and transpiration processes (Allen et al., 1998). ET can be calculated using many different formulas. Historically, the Blaney-Criddle method has been the dominant method used in the arid west of the United States and has been widely used in agricultural development work because it is the least data intensive method (Dunne and Leopold, 1978). It is used by the State of Colorado in their Decision Support System, by the NRCS (formerly the Soil Conservation Service) and by the Farm Service Agency (FSA). Therefore, the Blaney-Criddle method was deemed to be the appropriate method to use in calculating ET for this study. The major variables used in calculating ET in the Blaney-Criddle model are the index of energy available for ET, temperature and day-length (Dunne and Leopold, 1978). In 1970 the Blaney-Criddle variation used in this study was developed by the Soil Conservation Service (SCS, now known as the Natural Resource Conservation Service) to estimate short term values from 5 30 days. In order to accurately estimate these ET values the SCS incorporated two 23

24 modifications into the original formula: a climatic coefficient and a crop growth stage coefficient Effective Precipitation Effective precipitation (EP) has many definitions, based on needs and perspective (Dastane, 1978). The definition that will be used in this study is that which was defined by the SCS (U.S. Dept. of Agriculture, 1967). The SCS defines EP as precipitation which is received during the growing period of a crop and is available to meet consumptive water requirements (U.S. Dept. of Agriculture, 1967). Only water in the plants root zone is considered available for consumptive use. Deep percolation and surface runoff are not available to the plant, therefore are not included in EP. In 1970 the Soil Conservation Service calculated values for monthly effective precipitation based on 50 years of precipitation data from 22 weather stations across the nation. The method incorporates the monthly mean precipitation, the average monthly crop evapotranspiration rate, and soil water storage using a monthly time step (U.S. Department of Agriculture, 2007b). The monthly time step may be insufficient for detailed analysis or planning, such as irrigation scheduling, but is appropriate for general planning purposes at Boulder County Estimating Consumptive Use The consumptive use values are incorporated in the GIS to determine the irrigation water requirements for each agricultural field in the study area. These values are compared to irrigation water allocation values to determine if the allocation is appropriate for the agricultural production needs. There were three 24

25 sources for estimating crop consumptive use that were evaluated for this study: Irrigation Requirement Model (IWR) (U.S. Department of Agriculture, 2007a), the StateCU model from the Colorado Decision Support System (Colorado Division of Water Resources, 2007), and the Colorado Irrigation Guide (CIG) (U.S. Department of Agriculture,1988) (see Table 2.4) Irrigation Water Requirement Model The Irrigation Water Requirement (IWR) program, developed by the NRCS, is designed to calculate the monthly and seasonal irrigation requirement. The model uses local climate, crop, soils, and reference crop evapotranspiration data in its calculations. The IWR application does not have the capability to calculate daily irrigation requirements and it does not account for additional water requirements, such as leaching, salinity control, frost or heat control, or irrigation efficiencies. IWR uses three methods of calculating ET, depending on the data available: Blaney-Criddle TR-21, Temperature, and Radiation (FAO Blaney-Criddle) (U.S. Department of Agriculture, 2007a). A correction factor can be applied to the Blaney-Criddle TR-21 method to adjust for the effects of elevation in the calculation of ET. When applied, the correction factor increases the calculated ET amount by 10% for every 1000 meters above sea level (U.S. Department of Agriculture, 2007a). The Temperature and Radiation methods both account for elevation inherently in their formulas. 25

26 Colorado River Decision Support System The Colorado River Decision Support System (CRDSS) is a comprehensive management system designed to allow water users and managers in the State of Colorado a way to store and access a wide array of information about the Colorado River and its tributaries. The system includes three models: Colorado River Basin Simulation Model, a Water Resource Planning Model and a Consumptive Use Model (StateCU). The StateCU model was developed to calculate crop consumptive use. The model can run five analysis scenarios: Crop Irrigation Water Requirement by Location, Water Supply Limited Crop Consumptive Use by Structure, Water Supply Limited Crop Consumptive Use by Structure Considering Ground Water, Water Supply Limited Crop Consumptive Use by Structure and Priority, and Depletion by Structure and Priority (Colorado Division of Water Resources, 2004). StateCU can determine irrigation water requirements using a daily time step or using a monthly time step. The model has the ability to use three different methods to calculate the daily consumptive use values: Penman-Monteith, ASCE Standardized Penman-Monteith, and Modified Hargreaves. Monthly crop consumptive use can be calculated using either the SCS Blaney-Criddle (TR-21) method or the Pochop method (for bluegrass only) (Colorado Division of Water Resources, 2004). The Blaney-Criddle (TR-21) was modified by developing locally calibrated crop coefficients. Three sets of coefficients were developed, due to the wide 26

27 range in elevations: the High Plains (west of the foothills and generally over 6,500 feet), the Upper Plains (Water District 1, 2 and the eastern portions of Water Districts 3, 4, 5, 6, 7, 8 and 9), and the Lower Plains (Water District 64). (Wilson et al., 2005) Colorado Irrigation Guide (CIG) The Colorado Irrigation Guide was developed by the Soil Conservation Service to aid water managers and planners in Colorado in the decision making process when developing and managing irrigation water and systems (U. S. Department of Agriculture, 1988). The state is divided into seven zones, based on the consumptive use rate of alfalfa and grass pasture at the peak period (U. S. Department of Agriculture, 1988). Consumptive use rates are calculated using the Blaney-Criddle TR-21 method. Table 2.4 Comparison of programs that estimate crop evapotranspiration ( 1 U.S. Department of Agriculture, Natural Resources Conservation Services 2007a, 2 Colorado Division of Water Resources 2004, 3 U. S. Department of Agriculture, Soil Conservation Service 1988) Method of Calculating ET Modifications IWR1 CDSS2 CIG3 Monthly Blaney-Criddle TR-21 Temperature Radiation Daily Penman-Monteith ASCE Standardized Penman-Monteith Modified Hargreaves Monthly Blaney-Criddle TR-21 Pochop Monthly Blaney-Criddle TR-21 Elevation correction factor optional Locally calibrated For bluegrass only State divided in 7 zones 27

28 2.8. Summary The literature review reveals that while there has been considerable research done on using GIS for irrigation water management, most of the focus has been on applying GIS to irrigation scheduling or to water balance. The literature review reveals a gap in utilizing GIS to integrate irrigation efficiencies, crop irrigation water demand, and water allocation and then applying this spatial knowledge to the decision making process in an open space agricultural program with disparate properties and water sources. This is an area that would benefit from more research. 28

29 3. Chapter 3. A GIS for the Management of Agricultural Water Resources in the Boulder, County Parks and Open Space Program 3.1. Abstract As the demand for water along the Front Range of Colorado increases, the Boulder County Parks and Open Space (BCPOS) program must find ways to more effectively and efficiently manage its water resources to provide long term sustainability for its irrigated farms. Using GIS to explore and analyze the spatial distribution and relationships between and among agricultural and water information enables BCPOS to make more informed decisions about agricultural water management. This study develops and evaluates an integrated GIS for agricultural water management system in the Highland Study Area of Boulder County. This agricultural water management system incorporates existing spatial data, such as irrigation water supply infrastructure and agricultural fields, and non-spatial data, such as agricultural management activities conducted on open space agricultural properties. These data are integrated from a variety of sources, formats and models, such as the BCPOS Oracle databases, ESRI s SDE, and the Natural Resource Conservation Services (NRCS) Irrigation Water Requirement (IWR) model. All of these disparate datasets are integrated in ESRI s ArcGIS where spatial relationships are evaluated. The GIS calculates and ranks the 29

30 surplus and deficit of irrigation water, the on farm and off farm irrigation efficiencies and the overall agricultural irrigation efficiency. Results revealed that 71% of the 14 properties in the Highland Study were water short by 100 acre-feet or more for the crops grown in One property, Strawberry Holdings, had a water surplus of acre-feet. The Harless property and the Rocky Mountain Fuel 2 property were found to have the highest irrigation efficiencies, but also had the largest water deficits, and acre-feet, respectively. Results also showed that installing center pivot sprinklers, without also increasing the water supply, would not be sufficient to meet the irrigation water requirements. This study illustrates how the GIS can be a successful and effective water resource management tool for agricultural water resources in the open space program at Boulder County. Keywords Geographic Information System (GIS); agricultural water management; open space; agricultural efficiency; irrigation water 3.2. Introduction The population of Boulder County, Colorado is projected to increase from 285,880 to 385,667 between 2005 and 2035, an increase of over 25% (Colorado State Demography Office, 2008). In addition to population pressures within the County comes population growth within the South Platte River Basin, in which Boulder County is located. The population within the Basin was estimated to be 867,000 in 2000 and is projected to grow to 1,608,000 by the year 2030 (Interbasin Compact Committee, 2008). 30

31 Irrigation is a vital component of agriculture in Boulder County, supplying up to 87% of the seasonal crop water requirement in a normal precipitation year (U.S. Department of Agriculture, 2007a). With an increase in population comes an increased demand for municipal water in direct competition for agricultural water. There are over 1 million irrigated acres in the South Plate River Basin, most of which do not have a sufficient irrigation water supply (Interbasin Compact Committee, 2008). Without a sufficient supplemental water supply, irrigated crop production cannot be a viable enterprise on the Front Range as a farmer is limited in crop production choices due to the scarcity of agricultural water. As a local land management agency with a large water portfolio, the Boulder County Parks and Open Space (BCPOS) program has the responsibility to manage these water resources for diverse and sometimes competing purposes, including agricultural production, recreation and environmental health. The largest use of water in the open space system has been, and is likely to remain, the agriculture program, which encompasses 45% of the fee owned property and uses. Supporting and preserving local agriculture has always been of great importance to Boulder County. One objective of the 1978 Boulder County Comprehensive Plan is to promote and assist in the preservation of agricultural lands for agricultural and other rural purposes (Boulder County Land Use, 1999). The Parks and Open Space program is one tool which the county uses to achieve this objective. 31

32 One of the goals as stated in the Parks and Open Space Department Mission Statement is to promote and provide for sustainable agriculture in Boulder County for the natural, cultural and economic values it provides (Boulder County Parks and Open Space, 2007). The public continues to exhibit strong support for an agricultural program, lending justification to the department s long term commitment to creating a sustainable agricultural program. In a public opinion survey conducted in July 2002, over half of those surveyed responded that it was very important to preserve farms and ranches, and another 30 percent responded that it was fairly important (Public Information Corporation, 2005). In order to balance the public s desire for both a sustainable agricultural program and for recreational opportunities and environmental health, BCPOS strives to manage these limited water resources in the most efficient and effective manner possible. To do this requires a comprehensive understanding of large quantities of complex information, including resource ownership, legal constraints, climate conditions, land use status, water availability, irrigation distributions systems, management methods, program priorities and agricultural practices. All of this information is either land or water based, with a spatial distribution, naturally lending itself to use within a Geographic Information System (GIS). GIS offers many advantages in modeling water resources, and agricultural water in particular. GIS has the ability to simulate natural processes, to facilitate data organization, to process and analyze a large number of variables, to integrate data from many disparate sources, including external models, and to perform 32

33 repetitious processes, which enables various scenarios to be modeled and compared. In addition, GIS can perform all of these tasks in a time efficient manner (Lyon, 2003; Maidment and Djokic, 2000). Irrigation water models and GIS integration has been used for various applications, most commonly for modeling irrigation scheduling or irrigation requirements. Scheduling irrigation through the use of GIS has been applied to studies in India (George et al., 2004), Uzbekistan (Fortes et al., 2005), and several studies in Malaysia (Rowshoon et al., 2003; Ali et al., 2003). Assessment of the spatial distribution and demand of irrigation water requirements has been undertaken in a variety of locations, including Texas (Santhi et al., 2005), Wales (Knox and Weatherfield, 1999), Australia (Khan and Abbas, 2007), Brazil (Heinemann et al., 2002), and Crete (Tsanis and Naoum, 2003). These systems have integrated a number of models, including the agro-hydrological model Soil- Water-Atmosphere-Plant (SWAP), the hydrological model Soil and Water Assessment Tool (SWAT) and the crop model The Agricultural and Environmental Geographic Information System for Windows (AEGIS-WIN). This study presents the development and operational processes for an integrated GIS for the management of agricultural water resources at Boulder County Parks and Open Space. The goal was to design and test an integrated GIS to assess the spatial distribution of relative agricultural water use efficiency values at the property level. In order for the system to meet the needs of the end users and to ensure long-term functionality, key system requirements were identified. To be fully successful the integrated GIS must: 33

34 Be both spatially scalable and content scalable; Utilize existing GIS software components; Be based on existing spatial and non-spatial datasets; Store data in a format that is both compatible with the GIS software and the existing information technology structure; Provide flexibility in data access, manipulation and output. This paper details the pilot project used to develop and test a GIS for the management of agricultural water in the Highland Study Area in Boulder County. The datasets used, the GIS processes, the results of the spatial modeling process, and the conclusions regarding the assessment of the GIS for agricultural water management in Boulder County are discussed in this paper System Although BCPOS staff have identified numerous management questions and scenarios that the GIS is designed to address in the long term, a single management objective was chosen for this study to evaluate the model: to determine the spatial distribution of relative agricultural water use efficiency values at the property level. For the purposes of agricultural water management at Boulder County, agricultural water efficiency is defined as both minimizing the physical loss of water through the irrigation water delivery network and ensuring that there is the appropriate amount of water is available for a given cropping regime on each property. This particular scenario was chosen for two reasons. The first reason is the timeliness of the issue within Boulder County Parks and Open Space management 34

35 priorities. A process to define water management policy has begun to set strategic guidelines in regard to how water is managed at Parks and Open Space. The policy will initially focus on managing water use for agricultural production and for riparian health. Many of the goals and objectives identified in this process will rely on the output generated by this study. In addition, there are a number of imminent management decisions regarding agricultural water, including which water to purchase as it becomes available on the market and where to focus budget and staff time on infrastructure improvements, such as installing center pivot sprinklers or performing headgate repairs. The second reason is the scope of the components of the GIS which this management question incorporates. The study objective addresses all aspects and elements of the GIS with this single question, therefore the validity of the entire system can be determined. This ensures that the GIS will be correct in its structure, as well as scalable and broad enough to answer future management questions, and not be limited in scope. This GIS is intended to rank relative property efficiencies, not to quantify the amount of water loss or to micro-manage agricultural tasks, such as irrigation scheduling. The GIS is intended to be used by technical and non-technical County staff to examine agricultural water use within the Parks and Open Space system and to inform the agricultural water management decision-making process. The GIS effectively addresses the issue of spatial scale. The spatial scales for agricultural water management at Boulder County are agricultural fields, 35

36 agricultural properties, ditch company service areas, open space properties and the County (Figure 3.1, Table 3.1). The basic spatial unit is the agricultural field, which can be aggregated to attain different spatial scales, including the property level, the ditch service areas, property groups or eventually the whole county. The ability to aggregate spatial units allows flexibility in the system, because different management questions can be addressed at different spatial scales. For example, at the field level, spatial questions such as identifying the application method efficiency for a selected field or locating infrastructure in poor condition which serves that field can be investigated. At a coarser scale, properties can be identified where the condition of the infrastructure is decreasing the tenants ability to maximize productive potential or where a multi-field center pivot sprinkler might improve irrigation efficiency. Figure 3.1 Relationships of spatial units of agricultural water management components and their relationships in the Boulder County GIS 36

37 Table 3.1 Size ranges of spatial units in the Boulder County GIS, in acres Spatial Unit Minimum Maximum Mean Agricultural Fields Agricultural Properties Ditch Company Service Areas* , , Total Area Boulder County 474,363 *may extend outside of Boulder County 3.4. Data The GIS integrates data from various formats, locations and spatial scales (Table 3.2). All data integration, analysis and output is performed in ESRI s (Earth System Research Institute) ArcGIS 9.2 software. Figure 3.2 illustrates the basic framework of the GIS, including data sources, formats, and integration. Spatial data used in the GIS is primarily vector data, such as the agricultural field delineations and hydrological features. Tabular data resides mainly in Oracle relational databases, with some data stored as Geodatabase tables. 37

38 Table 3.2 Spatial and non-spatial data descriptions, sources, accuracy, and formats in the Boulder County GIS 38

39 Figure 3.2 General framework of the integrated GIS for managing agricultural water in the open space program at Boulder County Spatial Data Hydrologic Data Hydrologic data includes stream and ditches, lakes and reservoirs, irrigation ystem features such as headgates, ditch source points, and the delivery points of water to open space agricultural properties. In addition to these feature datasets, there is a geometric network used to trace the movement of water through this system. In the past, these data have been used mainly for locational purposes, such as identifying the locations of ditches. In the GIS, with the new geometric network, water movement capabilities can be examined, finding where water can run or 39

40 where water can be exchanged between water supply systems. In addition, hydrological features have links to incorporate the spatial data with internal County databases, including the Parks and Open Space Tracker database (Figure 3.5), and external databases, such as the Colorado Decision Support System s Hydrobase database (Figure 3.5). In the GIS, ditches were linked to tabular data via a unique identifier, to gain added information. For example, data could be linked to water appropriation dates or beneficial uses, such as irrigation or recreation Agricultural Data Agricultural data include agricultural field delineations that identify both active and inactive fields. These delineations were based not on ecological factors, but on agricultural management units, such as fields that are grazed, fields that are planted with irrigated crops, and fields that are farmed with non-irrigated crops. Agricultural fields are delineated using aerial photography, and are field checked by POS staff using GPS verification points. These fields are updated yearly, prior to the planting season. These agricultural datasets are used in conjunction with crop consumptive use to determine the irrigation water demand for agricultural fields and properties Open Space Data The Open Space data contains all parcels owned by Boulder County, municipalities, and Colorado state agencies. The majority of the federal lands, properties designated as watersheds, subdivisions, and private conservation 40

41 easements are contained in separate datasets. Each open space polygon is attributed with information such as the property s name and agency ownership. If the property is county owned, then additional information is collected, including date of purchase, usage type, and restrictions on public access Soils Data Soils data were taken from the NRCS Soil Survey Geographic (SSURGO) database, ranging from a scale of 1:12,000 to 1:63,360 (U.S. Department of Agriculture, 2006). The basic spatial unit is the soil mapping unit, which is generally equivalent to a soil phase. A soil phase is a classification that acknowledges the differences in soil characteristics that are important in managing soils, but not in classifying the soil type. These defining characteristics include slope and texture. All interpretive groups, such as the capability classification are based on aggregations of this soil mapping unit (U.S. Department of Agriculture, 2007c). Capability classification is the method that is used to broadly group soilmapping units based on their suitability and limitations for traditional farming practices. Capability classes are based on soil characteristics, which indicate that the soil subclasses or soil units have similar limitations for agricultural production. In general, the lower the capability class numerical value of the soil, the lower the steepness of the slope and the higher the permeability to water. Soils become less suitable for agriculture as the capability class numerical value increases (U.S. Department of Agriculture, 2007c). The capability class is used, 41

42 along with the field irrigation application method, to determine the irrigation efficiency values Non-Spatial Data The majority of the non-spatial, or tabular, data resides in one of two Oracle databases, an agricultural tracking database and a property and water ownership database. Additional datasets are housed in various external databases tables Agricultural Management Database (POSAG) BCPOS has an existing agricultural database that tracks information on all of the agricultural management activities that occur on open space properties. Information in this database includes the types of crops planted, the amount of irrigation water, fertilizer and pesticides applied to these crops, and the crop yield at harvest. The crop type is used to determine the irrigation water requirement for each field and property The agricultural database was designed to be spatially integrated with the agricultural fields geographic dataset. The Oracle database automatically validates against the spatial dataset daily to ensure that all of the links between tabular data and spatial data are synchronized. In addition, the database checks to make sure that the spatial data adhere to the database business rules, namely that all field identifiers in the spatial data are unique and valid. This database has complete records for the 2005 growing year in the Highland Study Area, which were used in the GIS. BCPOS is currently in the process of instituting a permanent procedure for all current and future data entry and validation into this database. 42

43 Parks & Open Space Ownership Database (Tracker) Boulder County Parks & Open Space also maintains an Oracle database that is designed to inventory and manage property, mineral and water rights owned by the County, as well as agricultural leases administered by BCPOS. In addition to the basic ownership information, there is a significant amount of information which describes the legal abilities and responsibilities of the county regarding these interest rights. Property interest detail includes information regarding the development rights sold from the property, mineral rights purchased with the property, grants obtained to complete the purchase, any improvements on the property, and the cost of the purchase. Information tracked regarding the water interests includes the amount of water owned, ownership type, the water supply company or organization, the water rights underlying that particular unit of ownership, historic yields for that water, the property the water was purchased in conjunction with, the location the water is currently being used at, and the annual ditch company assessments paid for that water. The lease component details lessee information, dates of the lease, and the rights and responsibilities of both the lessee and the lessor. The data from Tracker are used by the GIS to specify how much water will be available and allocated in any given year. In the past, this database has been used strictly as an inventory tool. Now, the data can link directly to spatial data contained within the GIS. There are multiple spatial features to which data can link, because the database contains such diverse pieces of information. For instance, both county water ownership interest information and water company information may be linked to each ditch. In 43

44 addition, water company data may be linked to the spatial datasets delineating ditch service areas and the points of diversion for each ditch (Figure 3.3). Figure 3.3 Various methods of linking spatial and tabular data in the Boulder County GIS using the ditch, the ditch diversion points, the ditch service areas, and the open space properties Colorado Decision Support System (Hydrobase) Hydrobase is a relational database developed by Colorado Water Conservation Board and the Colorado Division of Water Resources. The database houses information regarding stream flows, water diversions, and water rights in the water basins of Colorado. Associated tools have been developed to manipulate the data, including the StateCU model, which estimates crop consumptive use. 44

45 IWR (Irrigation Water Requirement) Model The Irrigation Water Requirement (IWR) program developed by the NRCS is designed to calculate the monthly and seasonal irrigation requirement. The model uses local climate, crop, soil, and reference crop evapotranspiration data in its calculations. The IWR model calculates precipitation values using local weather stations, as well as effective precipitation values, for both a normal precipitation year and a dry precipitation year. For Boulder County calculations, IWR utilizes Northern Colorado Water Conservancy District s ESE Longmont weather station data. These data were used to calculate the net irrigation requirement for each crop type grown in Boulder County. This requirement value is linked through the agricultural management database to the agricultural field spatial data, to calculate an irrigation water requirement per agricultural field. This water requirement can be used at the field level or can be aggregated to calculate a total property water requirement Other Tabular Data Additional tabular datasets are necessary to store data that link to spatial data. Field irrigation method efficiencies are stored in as an ESRI Geodatabase table. This table is linked to the agricultural fields table to spatially represent and calculate the field irrigation method efficiency for each field. Irrigation management capability rankings are also housed in a Geodatabase table. These values rank a farmer s irrigation management capabilities and links them to the 45

46 open space dataset. These values are the incorporated into the irrigation efficiency calculation Application In order to optimize the use of the water resources for agricultural production, BCPOS has defined agricultural water efficiency to be both minimizing the loss of irrigation water and supply the appropriate amount of water to farms for agricultural production needs. To determine the spatial distribution of these agricultural water use efficiency values utilizing GIS, there are three components which must be evaluated for each open space property: the relative irrigation system efficiency of the network serving that property, the total irrigation water requirement necessary to fully irrigate the property, and the irrigation water supply available for that property (Figure 3.4). For each step in the model, results are calculated. These results are ranked before going on to the next step. The project study area included 14 properties. Therefore, when each property is ranked the rankings range from 1 to 14, where 1 is the lowest value and 14 is the highest. These rankings represent a property s rank relative to another property. After the ranking values for each of the three components (irrigation efficiency, water requirement, and water supply) are calculated individually, these values are multiplied together. The range of possible values is from 1 to 196, resulting from the multiplied ranking values. This process calculates an overall agricultural efficiency ranking value. These various ranking values are used by BCPOS staff to better understand the 46

47 agricultural production system. This improved understanding helps staff make better informed decisions when managing agricultural water. Figure 3.4 Procedure for ranking total agricultural water efficiency in the Boulder County GIS Determining irrigation system efficiency In order to evaluate the overall irrigation efficiency of the irrigation water delivery system, the network can be divided into three physical components: the conveyance system, the distribution system and the field application (Bos and Nugteren, 1990). Water loss in any component of an irrigation system falls into three general categories: physical factors, management factors, and institutional and social factors (U. S. Department of the Interior, 1979). The variables defining irrigation efficiency for each of these physical irrigation system components differs, therefore each must be evaluated independently. 47

48 Social and institutional factors are not directly included in the GIS for several reasons. First, some of the components are difficult to capture in a GIS and are well beyond the need for this system, such as the financial capabilities of the managing entity or societal values. Second, some of the related pieces of information are housed within the water and property database, such as legal uses of a particular ownership unit of water. These pieces of data can be addressed through specific questions or queries performed in the GIS Property Conveyance Efficiency The conveyance system is the infrastructure that moves the water from its source through the main and lateral ditches to the farm. The evaluation factors for determining the conveyance system efficiency are the surface type of the structures, the condition and amount of vegetation in the system, and the quality of management by the system operators (U.S. Department of the Interior, 1979). The GIS uses the streams and ditches layer, the diversion points layer, the condition table and the surface type table to determine the conveyance system efficiency ranking for each ditch segment and diversion structure within the irrigation network. A geometric network is used to determine which ditch segments and diversion structures serve in the conveyance system for each property Property Distribution Efficiency The infrastructure that moves the water from the conveyance system to individual fields is considered the water distribution system. Distribution efficiency is calculated by the efficiency of the physical structures, the presence 48

49 of measurement structures, the farm layout, the level of maintenance on the system, and the level of irrigation management by the farmer (U.S. Department of the Interior, 1979). The distribution efficiency values are calculated similar to the conveyance efficiency values. The efficiency values are calculated for each ditch segment and diversion structure. The data are imported to the GIS and a geometric network was used to find the associations between delivery system components and the properties that they serve Property Application Efficiency The field application method is the manner in which the water is moved from the agricultural field inlet to the crop. Irrigation application efficiency is determined by the efficiency value of the irrigation method, the soil type, the slope of the field, and the management of the irrigation system by the farmer (U.S. Department of the Interior, 1979). To evaluate the efficiency ranking of the application system the GIS uses the soils capability class, the tenant management ranking table, the irrigation method efficiency table, the streams and ditches layer, and the diversion point layer. All are linked to the agricultural field dataset, in which an application efficiency ranking is calculated. An average field application efficiency ranking is determined for each property Irrigation Management Capability A farmer s management skills and abilities have a significant effect on the productive potential of one farm relative to another, even when the environmental and economic conditions are relatively equal. The management capacity is defined as having the appropriate personal characteristics and skill to deal with 49

50 the right problems and opportunities in the right moment in the right way (Ruogoor et al., 1998). One way to evaluate the management abilities of a farmer is to examine the explicit and measurable actions which are related to the decision making process (Ruogor et al., 1998). Good irrigation management demands that the farmer know when to irrigate, how much to irrigate, and how to operate and maintain the irrigation system (Hoffman, 1990). The measurable and observable actions or outcomes used to measure a farmers irrigation management abilities were: Maintaining good irrigation records Participating in NRCS Irrigation Water Management (IWM) planning Working with crop or irrigation consultants Maintaining equipment in good condition Maintaining irrigation system in good condition Using ET or soil moisture methods to monitor the irrigation requirement Minimizing tail water runoff Calculate Total Property Irrigation System Efficiency After the spatial distribution of the property efficiency values for each of the separate components is calculated, they are compiled to create a spatial distribution of the total irrigation system efficiency ranking for each agricultural property. 50

51 Determining irrigation water requirements The irrigation water requirement is calculated using the similar methodology to that which is laid out in both the NRCS IWR model and the FAO CROPWAT model. In fact, this study utilizes output from the IWR model, but takes the information and applies it spatially, which enables the crop water requirement information to be integrated with other spatial information. The basic irrigation water requirement calculation used in this study is: IWR = (CU - EP) * Ea * Agricultural Field Acreage (1) where CU = Crop Consumptive Use in AF EP = Effective Precipitation Ea = Field Irrigation Method Efficiency (1U.S. Department of Agriculture, 2007a; Allen et al., 1998) Crop consumptive use values are calculated in the NRCS IWR model. The IWR model uses the modified Blaney-Criddle method to calculate crop consumptive use. Historically, the Blaney-Criddle method has been the dominant method used in the arid west of the United States and has been widely used in agricultural development work (Dunne and Leopold, 1978). It is used by the State of Colorado in their Decision Support System, by the NRCS (formerly the Soil Conservation Service) and by the Farm Service Agency (FSA). Because all 51

52 of these entities have used, and still use, the Blaney-Criddle method, and the fact that Boulder County Parks and Open Space works extensively with these organizations, the Blaney-Criddle method was deemed the appropriate method to use in this study. Precipitation and effective precipitation figures for both a normal precipitation year and a dry precipitation year are calculated and incorporated into the model. A dry precipitation year is a year in which there is an 80% chance of the precipitation meeting or exceeding the calculated precipitation value. A normal precipitation year is a year in which the precipitation has a 50% chance of meeting or exceeding the calculated precipitation value (U.S. Department of Agriculture, 2007a). Calculating both climatic conditions allows staff the flexibility to run various management scenarios, including planning for drought situations Determining irrigation water supply The irrigation water supply is determined from the leased irrigation water. These quantities are specified amounts of water that the County will lease under contract to a farmer. An assumption made is that all of the water that is allocated to a farmer through the lease contract to be used on a particular farm is fully used. The leased water quantities are used in conjunction with the annual water yield values to calculate the predicted volume of water allocated by the system for each unit of ownership. In addition to water leased to the farmer from the County, there may be additional water that the tenant personally rents for the irrigation season from private individuals or entities. This rented water is not included in 52

53 the model, as one objective of Boulder County is to supply enough water to fully irrigate a farm, eliminating the need for a farmer to rent additional water supplies Calculate total agricultural efficiency Each component of the model, irrigation system efficiency, the irrigation water requirement, and the irrigation water supply, generates output. These intermediate output can be both tabular data, as in the case of the geometric network, or it can be thematic, as in the irrigation water demand per field. These intermediate output datasets can be used independently for decision making, such as determining where application method efficiencies are low, or they can be aggregated to a final thematic output, which is an overall relative ranking of agricultural water efficiencies of open space properties. This final thematic layer can be used to compare these relative total agricultural water efficiencies between properties Highland Case Study Study Area Description Boulder County is situated in northern Colorado, along the Front Range of the Rocky Mountains (Figure 3.5). The eastern half of the county lies on the high plains, with an average elevation of 5,250 feet. The western half of the county is mountainous, with the western boundary running along the continental divide, reaching the county s highest point of 14,255 feet at Longs Peak in Rocky Mountain National Park. 53

54 Figure 3.5 Boulder County, Colorado, USA In general, Boulder County s climate is semi-arid, with dry winters and the majority of the precipitation falling in early spring and summer (Peel, 2007; Western Regional Climate Center, 2008a). But, due to the extreme range in elevation, the climate of Boulder County varies greatly. Temperatures in Longmont range from an average low of 11.9º F to an average high of 88.9º F (Western Regional Climate Center, 2008b). Precipitation ranges from low of inches at locations along the plains to over 50 inches in the mountains, with an average precipitation of 16 inches at Longmont (Western Regional Climate Center, 2008c). The low amount of precipitation on the plains, where the most intensive human uses are located, forces Boulder County to rely heavily on the supply of surface water from snow pack in the mountains. In order to capitalize 54

55 on the snow melt which occurs during a short period in late spring and early summer, the area relies on a large and complex network of water storage facilities and distribution infrastructure (Figure 3.6). Figure 3.6 Water delivery system and watersheds in Boulder County, Colorado Boulder County has a land area of 473,907 acres, 107,629 (22.9%) of which are in agricultural production. Of those 107,629 acres in agricultural production, 50% is in cropland, roughly a quarter of which is irrigated. The remaining 50% of agricultural land is in non-crop production, primarily grazing lands. In 2006, the predominant crops being produced in Boulder County were barley, corn, hay and wheat, bringing in nearly $5 million in revenue (National Agricultural Statistics Service, 2007). 55

56 Sixty-seven percent of the entire county land area is protected through public ownership (Table 3.3). The largest land owner is the Federal government, which includes the Forest Service, the Bureau of Land Management, and the National Park Service. The City of Boulder and the County of Boulder are also substantial land owners. The County manages 57,727 acres in direct ownership and holds conservation easements on another 36,249 acres (Figure 3.7). A large portion, (44.6%) of the land owned and managed Boulder County is in agricultural production. Table 3.3 Protected Public Lands in Boulder County Owner Acreage Boulder County Open Space 57,727 Boulder County Conservation Easement 36,249 Municiple Open Space or Conservation Easement 52,548 Federal Lands 168,872 Other Protected Lands 4,500 Total Protected Lands 319,896 56

57 Figure 3.7 Land owned or managed by Boulder County Parks and Open Space and other publicly owned lands in Boulder County Boulder County owns water rights in 65 different incorporated ditch companies, 38 unincorporated ditch companies, as well as over 53 more directly held rights. Some of these water rights are among the first water appropriations in the state. Boulder County s earliest water right is the first appropriation of the New Consolidated Lower Boulder Ditch in Assessing the financial value of the portfolio is difficult, as water values fluctuate with the market, but an estimate places the value of all water rights in excess of $60 million (Boulder County Parks and Open Space, 2008). An area in the northeastern portion of Boulder County was chosen to be a pilot project on which to test the new, integrated GIS. The Highland Study Area encompasses roughly 16,000 acres (Figure 3.8). The Study Area is approximately 57

58 5 miles to the north of Longmont, Colorado. The study area includes all open space properties that are irrigated under the Highland Ditch system (Table 3.4). Figure 3.8 Highland Study Area, Boulder County Table 3.4 Properties included in the Highland Study Area and their characteristics (Source: Boulder County Parks and Open Space) Property Water Supply Property 2005 (Acre-Feet) Acreage Irrigated Acreage Barrett Barrett II Burchfield Carlson Clark (Alberta) Cushman Darby Enright Harless Hirschfeld RMF II RMF III Strawberry Holdings I & II Sullivan Total

59 In addition to the Highland Ditch water that irrigates these properties, there are five additional water sources that originate within the basin, which serve some or all of these properties: New ISH Ditch, Independent Reservoir, Rough & Ready Ditch, Pleasant Valley Reservoir (Terry Lake), and the Supply Ditch (Figure 3.8). The county owns a substantial amount of Northern Colorado Water Conservancy District (NCWCD) Colorado-Big Thompson (CBT) 1 project water in the Highland Study Area, which serves 940 acres of irrigated ground on 8 properties within the study area. CBT water is delivered via the St Vrain Supply Canal to St Vrain Creek. From St Vrain Creek the water can be run through existing delivery structures to water users. In the Highland Study Area, the Highland, the Supply, the New ISH and the Rough & Ready ditch companies all deliver CBT water. The Highland Study Area was chosen as a pilot project for several reasons. First, records for these properties and water companies were more complete and accessible than other areas in the county. Second, there are many properties irrigated by the Highland Ditch Company, and there are multiple additional water sources supply water to the Study Area. Together these factors increase the 1 The Colorado Big Thompson project manages and diverts water from the Upper Colorado River basin over the continental divide to the South Platte River basin. Water from the Colorado River is stored it in a series of reservoirs near Granby, then piped under Rocky Mountain National Park in a 13 mile tunnel to another series of reservoirs on the east side of the park. From these reservoirs the water is delivered to users along the Front Range. The CBT project was built by the Bureau of Reclamation in the early part of the 20 th century and is administered by the Northern Colorado Water Conservancy District. The CBT project provides supplemental water to 30 municipalities and more than 650,000 acres of farmland in northeastern Colorado. It delivers an average of 213,000 acre feet of water annually and is the largest trans-mountain diversion project in Colorado (Northern Colorado Water Conservancy District 2008). 59

60 complexity and better test the applicability and thoroughness of the GIS. The final reason for selecting the Highland Study Area as the pilot area was the productive potential of the properties in this study increases the interest of Boulder County Parks and Open Space managers to develop innovative tools for agricultural resource management Results Several scenarios were run to simulate different management alternatives. The purpose was to examine the effects of different management decisions and options on the agricultural water efficiencies (Table 3.5). Table 3.5 Descriptions of the scenarios run in the pilot project in the Highland Study Area Description Scenario 1 Scenario 2 Scenario 3 Scenario 4 Baseline scenario. All calculations run on data reported for Increase water supply on Harless and Rocky Mountain Fuel 2. Increase irrigation system efficiencies on Harless, Strawberry Holdings, Strawberry Holdings II, Barrett, and Rocky Mountain Fuel 2. Increase irrigation system management on all properties to fair or good. Scenario 5 Comparison of spatial scales. Scenario 1: Reported 2005 Conditions Scenario 1 was the baseline scenario. This scenario used all of the existing datasets, representing actual conditions on the ground for Table 3.6 summarizes the results of Scenario 1. 60

61 Table 3.6 Scenario 1 Results Summary 61

62 The GIS results showed that in 2005, Rocky Mountain Fuel 2, Carlson, Harless and Sullivan had the highest ranked irrigation system efficiencies (Figure 3.9). The GIS also found that the majority of the properties within the Highland Study Area had insufficient irrigation water allocated to crop production in 2005 (Figure 3.10 and Figure 3.11). Seventy-one percent of the properties had a deficit of 100 acre-feet or more, as calculated for a dry precipitation year. Harless and Rocky Mountain Fuel 2 had the largest water deficit, all greater than 200 acrefeet. Strawberry Holdings II had a surplus of roughly 39 acre-feet of irrigation water. The total agricultural efficiency ranking was calculated by combining the overall irrigation system efficiency and the surplus or deficit of irrigation water for each property. The GIS calculated that Barrett II, Carlson, Cushman, and Strawberry Holdings I & II had the highest ranking for total agricultural efficiency (Figure 3.11). 62

63 Figure 3.9 Scenario 1 irrigation system efficiency rankings. 13 (dark green) indicates high irrigation system efficiency, 1 (dark red) indicates low irrigation system efficiency. Figure 3.10 Scenario 1 irrigation water allocation surplus and deficit ranking. 14 (dark green) indicates a low surplus or deficit of irrigation water, 1 (dark red) indicates a high surplus or deficit. 63

64 Figure3.11 Scenario 1 total agricultural water use efficiency ranking. 14 (dark green) indicates high agricultural water use efficiency, 1 (dark red) indicates low agricultural water use efficiency. Scenario 2: Increased Water Supply Scenario 2 examines the results of a simulation that increases the water supply by 5 additional shares of Highland Ditch water on both the Harless and Rocky Mountain Fuel 2 properties. Under these conditions, the Harless property ranking for appropriate allocation of water rose from a ranking of 1 to a ranking of 7. Rocky Mountain Fuel moved 2 to 8 (Figure 3.10 and Figure 3.12). Even though the additional water supply only increased the appropriate water allocation ranking to mid range, the effect on the ranking of overall efficiency was significant. Harless rose from a rank of 1 to 12, and Rocky Mountain Fuel 2 rose from a rank of 5 to 14 (Figure 3.11 and Figure 3.13). 64

65 Figure 3.12 Scenario 2 irrigation water allocation surplus and deficit ranking. 14 (dark green) indicates a low surplus or deficit of irrigation water, 1 (dark red) indicates a high surplus or deficit. Figure 3.13 Scenario 2 total agricultural water use efficiency ranking. 14 (dark green) indicates high agricultural water use efficiency, 1 (dark red) indicates low agricultural water use efficiency. 65

66 Scenario 3: Water Efficient Infrastructure Center pivot sprinkler systems have the potential to be up to 45% more efficient than graded furrow flood irrigation systems (Howell, 2003). BCPOS staff wanted to explore management scenarios where more efficient water application systems were implemented, as opposed to increasing the water supply. Scenario 3 simulates replacing the flood irrigation systems on Harless, Strawberry Holdings and Strawberry Holdings II, Barrett, and Rocky Mountain Fuel III with center pivot sprinklers. In this scenario the GIS found that Harless, Barrett, and Rocky Mountain Fuel 2 decreased their irrigation water deficit values, from 15 35%. Strawberry Holdings I and II increased its surplus of water by 38.66% (Table 3.7). Comparing the total agricultural irrigation water efficiency ranking results of Scenario 3 to the baseline results of Figure 3.13, staff could easily see that increasing the water supply had a bigger impact on the overall efficiency ranking that did the installation of a center pivot sprinkler on Harless and Rocky Mountain Fuel 3. Installing a center pivot sprinkler did increase the agricultural efficiency on the Barrett property, from 3 to 5 (Figure 3.11 and Figure 3.14). 66

67 Figure 3.14 Scenario 3 total agricultural water use efficiency ranking. 14 (dark green) indicates high agricultural water use efficiency, 1 (dark red) indicates low agricultural water use efficiency. 67

68 Table 3.7 Comparison of irrigation water surplus and deficit values between scenarios 1, 2, and 3 68

69 Scenario 4: Comparing Spatial Scale George et al. (2004) demonstrated that a GIS can be successfully used for irrigation scheduling and agricultural water management at different spatial scales. Scenario 4 illustrates the Boulder County GIS ability to use data at several spatial scales to address different management questions. Figure 3.15 shows the physical condition of all of the ditches included in the property water delivery systems. This information is useful to determine the condition of specific ditch segments. Figure 3.16 aggregates the condition of the ditch segments up to the fields that they serve. This provides an average delivery system condition ranking for each field. For example, a management question may be focused at the property level, such as which fields on the Harless property are the least efficient and may require improvement. In this case, using the field level average delivery system condition values are necessary. After managers determine which fields have the lowest efficiency or the highest productive potential, the conditions of each ditch segment can be utilized to prioritize maintenance. Running additional scenarios varying the management alternatives, such as lining a ditch segment or piping a ditch segment, will help managers in the decision making process. 69

70 Figure3.15 Physical condition of ditches in the Highland Study Area. Figure 3.16 Field level irrigation delivery system conditions calculated by averaging the conditions of all structures that serve each field 70