CHARACTERIZING DROUGHT IN IRRIGATED AGRICULTURAL SYSTEMS: THE SURFACE WATER DELIVERY INDEX (SWDI) 1

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1 Vol. 52, No. 3 AMERICAN WATER RESOURCES ASSOCIATION June 2016 CHARACTERIZING DROUGHT IN IRRIGATED AGRICULTURAL SYSTEMS: THE SURFACE WATER DELIVERY INDEX (SWDI) 1 David J. Hoekema and Jae Hyeon Ryu 2 ABSTRACT: Quantifying surface water shortages in arid and semiarid agricultural regions is challenging because limited water supplies are distributed over long distances based on complex water management systems constrained by legal, economic, and social frameworks that evolve with time. In such regions, the water supply is often derived in a climate dramatically different from where the water is diverted to meet agricultural demand. The existing drought indices which rely on local climate do not portray the complexities of the economic and legal constraints on water delivery. Nor do these indices quantify the shortages that occur in drought. Therefore, this research proposes a methodological approach to define surface water shortages in irrigated agricultural systems using a newly developed index termed the Surface Water Delivery Index (SWDI). The SWDI can be used to uniformly quantify surface water deficits/shortages at the end of the irrigation season. Results from the SWDI clearly illustrate how water shortages in droughts identified by the existing indices (e.g., SPI and PDSI) vary strongly both within and between basins. Some surface water entities are much more prone to water shortages than other entities based both on their source of water supply and water right portfolios. (KEY TERMS: irrigation; drought; water supply; water use.) Hoekema, David J. and Jae Hyeon Ryu, Characterizing Drought in Irrigated Agricultural Systems: The Surface Water Delivery Index (SWDI). Journal of the American Water Resources Association () 52 (3): DOI: / INTRODUCTION Quantification of surface water shortages in arid and semi arid regions that depend on surface water diversions to meet agricultural demand is a significant challenge in water management. For example, every year since 2005 the Director of the Idaho Department of Water Resources (IDWR) has sought to manage groundwater and surface water conjunctively for the administration of senior surface water rights in the central Snake River Plain (Schroeder, 2008; Spackman, 2010). Conjunctive water management refers to the requirement established by the 1994 Musser vs. Higginson case before the Idaho Supreme Court, that the Director of the IDWR must apply prior appropriation in the administration of hydraulically connected groundwater and surface water sources (Carlquist, 2008). The need for conjunctive management of senior surface water rights in central Idaho arose from a water call by the Surface Water Coalition (SWC) in 2005 (Schroeder, 2008), seeking the curtailment of thousands of hectares of land irrigated by water pumped from the East Snake 1 Paper No P of the Journal of the American Water Resources Association (). Received March 3, 2015; accepted March 1, American Water Resources Association. Discussions are open until six months from issue publication. 2 Hydrologist (Hoekema), Technical Bureau, Idaho Department of Water Resources, Boise, Idaho 83702; and Assistant Professor (Ryu), Department of Biological and Agricultural Engineering, University of Idaho, 322 E Front St., Boise, Idaho ( /Ryu: jryu@uidaho.edu). 737

2 HOEKEMA AND RYU Plain Aquifer (ESPA). Groundwater pumping in the ESPA depletes flow in the Snake River, which the SWC depends on. The outflow from the ESPA along the mainstem of the Snake River has decreased by roughly billion cubic meters per year above the American Falls Reservoir if measured between the Snake River nr Shelley, ID USGS gage to the Snake River nr Blackfoot, ID USGS gage The SWC is composed of seven canal companies and irrigation districts with surface water rights senior to most groundwater pumpers in the eastern Snake River Plain. One of the major challenges the Director faces each year is to determine if a surface water shortage is likely to occur, and how severe the water shortage will be to surface water irrigators. Based on the Director s decision, groundwater pumpers have to purchase or have ready an adequate supply of surface water to mitigate the surface water irrigators shortage caused by groundwater pumping. A surface water shortage in this context is defined as the deficit between the water diverted to meet the crop water demand of a normalized crop mix within an irrigation entity s place of use and the actual diversions by that entity, while the irrigation entity refers to any user of water for irrigation who diverts their water from a specified point of diversion to an identified place of use. As a base for determining if a shortage is likely to occur, the director of IDWR has sought to determine what a normal water supply should be for the SWC. Answering this question is not simple because water demand each year varies depending on many factors, such as climate variability, crop mix, rotation schedules, economic trends, and water supply uncertainty. As such, the water supply that was needed to meet a normal crop water demand 10 years ago may not be the same water supply needed under today s conditions due to climate variability, land use change, water conservation practices, and market trends. Since the 1990s, the dairy industry has grown dramatically in Idaho, driving up the demand for alfalfa and corn, especially silage corn. Traditionally, drought has almost always been defined in some manner that relates drought directly to a shortage of water, yet to our knowledge there are currently no drought indices that readily define the percentage of the water shortage that occurs in irrigated agricultural systems relying on surface water diversions. Therefore, an index that addresses water shortages at a fine enough scale to differentiate water deficits at the surface water diversions scale is critical to recognize, understand, and assess drought risk and impacts at the management scale (Ryu et al., 2014). In discussing drought, farmers in the Snake River Plain have often expressed frustration that broad-brush approaches to drought monitoring at the basin scale or county scale fail to differentiate between water limitations that vary across short distance caused by the varying water rights, water supply sources, and storage contracts between adjoining irrigation entities. While it should be noted that the Surface Water Delivery Index (SWDI) presented in this article is applied to and quantifies the deficit experienced by nine irrigation districts and canal companies located in the central Snake River Plain, the shortages described herein do not meet the legal and technical requirements needed to address the specific issue of the Surface Water Coalition Delivery Call in Idaho. Rather than focus on a specific administrative issue, this article explores ways to characterize water deficits in irrigated agricultural systems. Additionally, the proposed index, SWDI, also has the advantage that it can be uniformly applied across basins with varying water supplies at a diversion scale where the water right portfolio of the diversion entity and access to storage water may impact the severity of drought. These aspects are not addressed in the existing drought indices commonly applied in the United States, including the Standardized Precipitation Index (SPI, McKee et al., 1993), the Palmer Drought Severity Index (PDSI, Palmer, 1965), and the Surface Water Supply Index (SWSI, Shafer and Dezman, 1982; Garen, 1993). To the best of our knowledge a drought index has never been designed for application at the diversion entity scale. While PDSI, SPI, and SWSI provide a broad-brush approach at drought monitoring utilizing a county or basin scale, SWDI focuses on small, local management areas where local water management decisions are made. Currently, the most popular drought index among farmers in the Snake River Plain is the SWSI. The SWSI is a very useful index because it quantifies water supply at the basin scale based on current reservoir storage and predicted runoff from the mountain snowpack through the end of the irrigation season. The Natural Resource Conservation Service (NRCS) provides monthly SWSI values for 19 Idaho basins with five exceedance probabilities. The SWSI values are updated monthly from January through September using Garen s (1993) refined SWSI algorithm. Because the SWSI values are basin specific, the NRCS sets basin specific adequate water supply thresholds for most of Idaho s basins (NRCS, 2014). Most irrigators the authors are familiar with pay less attention to the PDSI and SPI. The PDSI has welldocumented limitations (Alley, 1984; Karl, 1986; Guttman, 1998). However, the authors have found significant correlation between SWSI and July/ August PDSI values in the Snake River basin, which confirms that PDSI has value as a general indicator 738

3 CHARACTERIZING DROUGHT IN IRRIGATED AGRICULTURAL SYSTEMS: THE SURFACE WATER DELIVERY INDEX (SWDI) of drought conditions. Hoekema and Sridhar (2011) found the Z-index used in the calculation of PDSI to be a good indicator for early season diversions. SPI is a poor indicator of drought for irrigated agriculture in the Snake River basin because rainfall is generally sparse throughout the irrigation season. The 12-month SPI, in particular, does have limited correlation with SWSI and PDSI since it generally represents seasonal water supply. Its use is limited mostly because it treats all precipitation equally, when snow in the winter time generally is of much greater value than rain in the western United States. There is one obvious limitation of the proposed SWDI in the sense that water deficits are determined by actual managed diversions. As such, diversions may vary over time due to changes in land use, cropping patterns, and irrigation technology. However, based on the authors experience, sudden changes in water demand outside of supply limitations are rare and can usually be identified to a specific cause. An irrigation entity typically tries to utilize as much water as possible, since irrigation in its simplest economic terms can be defined as a two step conversion from water to money. First the diverted water is converted to a crop and the crop is converted to money. Wasting water is therefore usually not in the interest of the irrigator and water conservation can lead to significant economic benefits. In a study on the economic impacts of water conservation on the Salmon Tract, Hoekema and Ryu (2013) utilized a present crop mix that irrigators indicated they applied to handle drought conditions. Irrigators in the Salmon Tract indicated significant changes in crop mix based on water supply forecasts. Even though that crop mix was based on present practices, the water demand of the current crop mixes was applied from 1910 to the present in order to drive reservoir operations. Although crop mix changed dramatically during this time period, they found that crop mix represented a proxy for full utilization of supply and they found that reservoir operations could be successfully replicated using current crop mix-based drought management. Another study by Hoekema and Sridhar (2011) utilized a stepwise relationship that is revealed by plotting SWSI values vs. diversion rates for canals across the Snake River from 1971 to As water supply (or SWSI value) increased, diversions increased until a threshold was reached. After that, threshold diversion rates were nearly constant. In other words, once the threshold at the end of the increasing limb of the relationship was exceeded, the full water supply of the canal company was attained. Hoekema and Sridhar (2011) found that construction of a reservoir could significantly alter the stepwise function between SWSI and diversion rates, and gradual reductions in diversions by some entities is leading to greater water supply reliability. The idea of the stepwise relationship between diversions was introduced to the authors by a comparison of regional diversions to SWSI by Scott (2010). Jeffers (2013) also applied the concept at a regional diversion scale. Trends in reduced diversions can be accounted for and corrected with a trend analysis in a deficit-based index. Sudden changes in demand, therefore, will always be a weakness in a diversion-based approach to determining water shortages in a managed system. In order to accurately identify the surface water deficit in a region that relies on surface water supply, the amount of water diverted should be compared to a climatically derived crop water demand. The crop water demand in any year should reflect the normal crop water demand in years with a full irrigation supply. The SWDI is derived by tracking agricultural diversions and comparing the diversions to crop water demand determined through use of the ASCE- EWRI 2005 standardized reference evapotranspiration equation (EWRI, 2005) and an irrigation model. The premise of the index we have derived is that the water deficit in a region irrigated by surface water supplies should be defined by the ability to divert an adequate quantity of water to meet the water demand of a normal crop mix. The actual diversion rates applied against crop water demand are assumed to contain all the economic, social, and legal constraints limiting surface water deliveries to the given irrigation entity. The goal of the proposed SWDI is not the identification of drought, but the identification of the impacts of drought and the frequency and severity of drought impacts on irrigation entities uniformly across basins. The SWDI is intended to be run at the end of an irrigation season to determine the surface water delivery deficit. Over multiple years, the index can help characterize the vulnerability of irrigation entities to drought. Note that while many or a few water users within each irrigation entity may have groundwater rights, we do not consider groundwater use in the calculation of SWDI. SWDI specifically addresses only deficits of water diverted from surface sources. While supplemental groundwater supplies have often been utilized to reduce drought impacts under severe drought conditions, it is well recognized that supplemental groundwater use in drought exacerbates aquifer declines and reduces the surface water supply both within the current season and future seasons depending on the response time of the aquifer. Before proceeding to discuss the development of the drought index in the Methodology section, background information of the study area is first described. In the Results portion of the article, we 739

4 HOEKEMA AND RYU evaluate the vulnerability of the nine surface water irrigation entities to droughts identified by the existing drought indices, including SPI, PDSI, and SWSI. At the end of the article we provide some concluding comments about the strengths and limitations of the new index. STUDY AREA The study area is composed of nine surface water irrigation entities located within the central Snake River Plain. These nine surface water irrigation entities (with a service area of 263,000 hectares) are located in the central portion of the Snake River Plain below American Falls Reservoir and above King Hill (Figure 1). The Snake River Plain stretches across southern Idaho from Wyoming to the Oregon border. A significant amount of incidental recharge from surface water irrigators in the Upper Snake River Plain above American Falls Reservoir and other natural sources of recharge provide a base flow from the ESPA to the Snake River above American Falls Reservoir of 2,200 Mm 3 /annually or an average rate of 71 cms (IDWR, 2013). Table 1 contrasts the climate averages from the Twin Falls and Rupert Agrimet Stations located in the irrigated regions where water is diverted and climate averages from four Snotel stations located in the mountainous regions from which the water supply is derived: Pole Creek Ranger Station, NV; Dollarhide Summit, ID; Lewis Lake Divide, WY; and Island Park, ID. The central Snake River Plain was the last major agricultural region developed in southern Idaho. While some irrigated land was developed within the Snake River Canyon and along the Big Wood and Little Wood rivers in the late 1800s, extensive agricultural development in the region began with the construction of Milner Dam (completed in 1905) and Minidoka Dam (completed in 1906). Diversions at these two dams provide water to seven irrigation entities, including (1) A&B Irrigation District (A&B), (2) American Falls Reservoir District #2 (AFRD2), (3) Burley Irrigation District (BID), (4) Milner Irrigation District (Milner), (5) Minidoka Irrigation District (MID), (6) North Side Canal Company (NSCC), and (7) Twin Falls Canal Company (TFCC). In addition to FIGURE 1. Map Showing the Nine Irrigation Entities within the Study Area: The A&B Irrigation District (A&B ID), the American Falls Reservoir District #2 (AFRD2), the Big Wood Canal Company (BWCC), Burley Irrigation District (BID), Milner Irrigation District (Milner ID), Minidoka Irrigation District (MID), North Side Canal Company (NSCC), Salmon River Canal Company (SRCC), and the Twin Falls Canal Company (TFCC). The entities are located in the central Snake River Plain at the west end of the East Snake Plain Aquifer (ESPA), the arrows in the basin show groundwater flow direction and point to the aquifer s major discharge locations. 740

5 CHARACTERIZING DROUGHT IN IRRIGATED AGRICULTURAL SYSTEMS: THE SURFACE WATER DELIVERY INDEX (SWDI) TABLE 1. Comparison of Climate Averages from 1991 to 2010 at Six Climate Stations. Station January February March April May June July August September October November December Annual Twin Falls T min ( C) Elev. 1,195 m T max ( C) PP (mm) Rupert T min ( C) Elev. 1,266 m T max ( C) PP (mm) Pole Creek T min ( C) Elev. 2,539 m T max ( C) PP Dollarhide T min ( C) Elev. 2,566 m T max ( C) PP (mm) Lewis Lake T min ( C) Elev. 2,393 m T max ( C) PP Island Park T min ( C) Elev. 1,917 m T max ( C) PP (mm) the seven irrigation entities that divert from the Snake River in southern Idaho, (8) the Salmon River Canal Company (SRCC) diverts irrigation water from the Salmon Falls Creek and (9) the Big Wood Canal Company (BWCC) diverts irrigation water from the Big and Little Wood rivers. The success of the privately funded TFCC in providing a reasonable irrigation supply to thousands of hectares of desert land, led to an irrigation development boom in southern Idaho (Lovin, 1987) in which a number of irrigated tracts were developed with inadequate water supply. For example, over 32,000 hectares of irrigable land was sold to settlers on the Salmon Tract prior to completion of the Salmon Falls Dam in 1911 (Lovin, 1986). During construction of the dam, canals and laterals to irrigate 61,000 hectares were constructed (Owens, 1999). By 1919, grossly inadequate water supplies and the ensuing legal actions reduced the tract to 14,164 hectares (Lovin, 1986). Canal company records indicate that adequate irrigation has only been provided in about half the years since The NSCC and BWCC would likely have suffered a similar fate had those tracts not been rescued by the expansion of the US Bureau of Reclamation (USBR) Minidoka Project on the Snake River through the construction of American Falls Dam in The rescue of the Big Wood Tract irrigated by BWCC was made possible by the construction of the Milner-Gooding Canal which stretches across 110 km of desert land to convey Snake River water from the Milner pool to irrigated tracts along the Little and Big Wood rivers. The Big Wood Tract, was split for administrative purposes between the BWCC irrigated lands and lands irrigated by the AFRD2. Today the BWCC diverts storage water from Magic Reservoir on the Big Wood River and natural flow from the Big Wood and Little Wood River to the North Shoshone, Richfield, and Dietrich irrigation tracts (BWCC, 2014). Natural flow is a term used in priority water rights administration that represents the calculated flow of what would be in the river had no water been stored or diverted upstream of a given location. Water cannot be stored during the irrigation season in a reservoir until all demands of those with natural flow rights senior to the storage right of the reservoir have been met. Figure 1 shows the boundaries of the BWCC as being located upstream and above the Milner-Gooding Canal which diverts water for AFRD2. However, it should be noted that the legal boundaries of AFRD2 and BWCC as defined by the water rights are almost completely overlapping. Completion of Palisades Dam in 1956 further shored up water supply for the NSCC and the Minidoka Project by providing supplemental irrigation to over 270,000 hectares. Development of the pump station for A&B Irrigation District in 1956, 741

6 HOEKEMA AND RYU which lifts water from the Milner pool to irrigate 6,000 hectares, completed the majority of surface water development in central Idaho. The surface irrigators in the region have historically relied heavily on natural flow emerging from the underlying ESPA into and near the American Falls Reservoir as well as stored water captured during the winter and the spring freshet in three major reservoirs: Jackson Lake in Wyoming, Palisades Reservoir on the Idaho-Wyoming border, and American Falls Reservoir. The ESPA is a highly permeable aquifer composed of relatively thin basalt flows (IDWR, 2013). Water flows through the aquifer in a southwesterly direction roughly parallel to the course of the Snake River which flows along the southern boundary of the Snake River Plain. Development of surface water irrigation, which was mostly accomplished by gravity irrigation methods in the early years, resulted in a large amount of incidental recharge that is estimated to have increased groundwater storage in the ESPA by 18,500 Mm 3 (Johnson et al., 1999). Discharge from the aquifer is estimated to have increased by 54 cms below Milner Dam from 1915 to The gains in the Snake River within this reach due to incidental recharge have nearly been erased by a reduction in recharge caused by surface water conservation, an expansion of groundwater pumping, and drought. Following World War II, the extensive development of groundwater-based irrigation, pressurized irrigation, and significant efforts to decrease conveyance loss and extensive droughts in the 1990s and 2000s are thought to be the main reasons of declining ESPA discharge (Johnson et al., 1999; IDWR, 2013). IDWR staff members estimate that the storage in the ESPA has declined by 14,800 Mm 3 since 1960s (Memo from M. McVay, April 14, 2014, Non-trust water area as it relates to the Eastern Snake Plain Aquifer, personal communication). According to the Snake River at Heise, June SWSI water shortages have occurred in 7 out of the 22 years between 1991 and The two years with the greatest shortages occurred in 1992 and The year 2001 was the first year of a four-year drought. The 1992 drought was toward the end of a dry period that stretched from 1988 to Both the early 1990s drought and early 2000s drought resulted in significant declines in the ESPA water levels. While the general pattern of drought is similar between the Snake River basin and the two tributary basins (Salmon Falls Creek and the Big Wood River) water shortages based on the agricultural thresholds set by the NRCS are more frequent in the tributary basins. Water shortages occurred nine times in both the Big Wood and Salmon Falls Creek basins according to SWSI. Like the Snake River basin the most severe droughts occurred in 1992 and The main discharge from the ESPA to the Snake River occurs in and above American Falls Reservoir in an area referred to as the Fort Hall Bottoms (Stearns et al., 1938). Stearns et al. (1938) reported that discharge from the aquifer in this region was thought to be 40 cm. The State of Idaho s groundwater model of the ESPA estimates that discharge was 71 cm at the beginning of the 1980s but has since declined by 14 cm (IDWR, 2013). The discharge of the ESPA in the Fort Hall Bottoms is very difficult to estimate because of the complex interactions with nearby irrigation tracts, the shallow groundwater table, and the existence of the American Falls Reservoir (Stene, 1997) that floods some of the springs when the reservoir fills. In summary, each of the irrigation entities within the study area has a unique history and water supply based on that history. The SRCC and BWCC which depend on tributaries of the Snake River to supply their irrigation water have a less reliable water supply than the other surface water entities. However, even the companies and water districts that rely on the Snake River for their water supply have strongly disparate water right portfolios. TFCC relies almost entirely on natural flow, while the other companies rely on a mix of junior water rights and storage contracts within USBR-operated reservoirs. Another factor affecting the water supply of these entities is their size. These entities also range in size from 82,000 hectares to 6,000 hectares. As such, it would be expected that each surface water irrigation entity is impacted by drought in different ways. The SWDI seeks to quantify the irrigation shortfall experienced by each entity during drought years. METHODOLOGY The premise of the SWDI is to divide the water diverted in a season, W diversion [Mm 3 ], by the seasonal crop water need, W need [mm], multiplied by the service area, A [hectares], and an adjustment factor, F [unitless]. Thus, the SWDI can be defined by Equation (1): SWDI ¼ W diversion W need A=F ð1þ We propose six categorizations for the SWDI index as such: (1) Normal Conditions when SWDI is greater than 0.9 (e.g., greater than 90% of the water demand is met), (2) Abnormally Dry if SWDI is between 0.80 and 0.89, (3) Moderate Drought when SWDI is between 0.7 and 0.79, (4) Severe Drought when 742

7 CHARACTERIZING DROUGHT IN IRRIGATED AGRICULTURAL SYSTEMS: THE SURFACE WATER DELIVERY INDEX (SWDI) SWDI is between 0.6 and 0.69, (5) Extreme Drought when SWDI is less than , and (6) Exceptional Drought when SWDI less than While the drought levels are labeled according to the classification scheme of the United States Drought Monitor (USDM, 2015), drought in the SWDI is defined by a physical relationship between water supply and demand rather than a statistical relationship. This categorization of drought was also justified based on discussions with irrigators in the Salmon River Tract. Irrigators in the Salmon Tract indicated that they can grow a reasonable crop if they receive at least 70% of their water allotment. It should be noted that the severity of a water shortage for various user groups may vary based on their water supply. Users who have a highly reliable water supply are more likely to be affected by smaller water shortages than those who have a less reliable water supply. Therefore, SWDI cannot predict the severity of drought as experienced by an irrigator, but the severity of the water shortage as compared to the normal water demand of a canal company or irrigation district s normal water demand. Water Diversions (W diversion ) and Service Area (A) Seasonal diversions, W diversion, records were based on daily diversion data downloaded from IDWR s water right accounting database ( qwraccounting/wra_select.aspx), the Bureau of Reclamation s Hydromet ( dromet), and the USGS database ( usgs.gov/nwis/dv/referred_module=sw). The only diversion records that were not available online were the diversion data for the BWCC, which were digitized from watermaster records at IDWR known as the black books. The service area of all the irrigation entities (A), except for the SRCC, was derived from the latest watermaster records. The service area of the SRCC was based on the SRCC website ( dam.com). mean daily humidity (Rh), mean daily dew point temperature (T dew ), and daily average wind speed (u 2 ). The calculation of reference ET (ET rs ) was based on the tall surfaces standard established by EWRI-ASCE (EWRI, 2005). The details of the ET rs calculations are contained in Appendix. After calculating ET rs, crop water need, W need, was calculated based on two irrigation models. Each irrigation model contains the components shown in Figure 2. The irrigation models were set up as two layer soil moisture models similar to Palmer s two layer bucket model (Palmer, 1965). In the models, soil moisture is added to the first soil layer as either precipitation, P (mm) or irrigations, I (mm). The first soil layer has a depth of 0.1 m. P is partitioned based on T min between rain, P rain (mm), and snow, P snow (mm). If T min exceeds 3.3 C (T rain ) all precipitation is considered to be rain, if T min is less than 1.0 C (T snow ) all the precipitation is considered as snow. Between T snow and T rain the P is considered as mixed based on a linear relationship between the percentage of rain and snow. Snowmelt occurs at a rate of 1 mm/ C when T max exceeds 0 C. Water can exit the upper soil layer as runoff if the infiltration rate is exceeded; evaporate, transpire, or seep into the deeper soil layer when the field capacity (0.23) of the upper soil layer is exceeded. Evaporation and transpiration processes were calculated based on the dual crop coefficient method established by FAO- 56 (Allen et al., 1998). In the second soil layer which is 1.9 m, water only enters from the upper layer and leaves either by transpiration (Equation 2) or deep Snow Rain Irriga on Evapora on Snow Alfalfa First Soil Moisture Layer Transpira on 10 cm Crop Water Need (W need ) Following data collection, we calculated crop water need, W need, based on a calculation of reference evapotranspiration using ASCE-EWRI 2005 method (EWRI, 2005) and the dual crop coefficient method established by FAO-56 (Allen et al., 1998). Daily reference evapotranspiration (ET) were calculated using climatic data from the Twin Falls and Rupert Agrimet Stations. The climatic data include minimum temperature (T min ), maximum temperature (T max ), average daily temperature (T), daily precipitation (P), Water Infiltrates the 2 nd soil Layer when the first reaches satura on Second Soil Moisture Layer FIGURE 2. Conceptual Diagram of the Two Layer Irrigation Model Used for the SWDI Calculation. 90 cm 743

8 HOEKEMA AND RYU recharge when field capacity is exceeded. Therefore, in the second soil layer (Equation 3) is modified so as to remove the evaporative component. K cb for uncut alfalfa was established by cumulative growing degree days, as per Allen and Robison (2007). However, it should be noted that both K cb and K e are limited by available soil moisture, the details of which are fully described in FAO-56 (Allen et al., 1998). ET crop;layer1 ¼ðK e þ K cb ÞET rs ð2þ ET crop = evapotranspiration of the crop (mm/day), K e = soil water evaporation coefficient (dimensionless), K cb = basal crop coefficient (dimensonless), ET rs = tall surface standardized reference evapotranspiration equation (mm/day). ET crop;layer2 ¼ K cb ET rs W need was calculated as a volume of water based on the number of irrigations needed per season and an irrigation rate through two different irrigation schemes. The numbers of irrigations per season were first determined by use of a crop water demand model, which is referred to as the Ideal Irrigation Scheme (IIS). IIS calculates the crop water demand for an optimally irrigated field of uncut alfalfa irrigated by a 393 m center pivot with a maximum rotation speed of once every three days and a flow rate of 4,158 L/min, or an application rate not to exceed 37 mm/day every three days. The model seeks to maintain the combined soil moisture in the soil layers above 180 mm throughout the irrigation season as defined by the water rights, which is generally from March 15 to November 15. The combined soil depth of the soil layers is 2 m, field capacity is 0.23, and the wilting point is Note that field capacity and wilting point are unitless. By iteration, it was determined that 180 mm was a reasonable value to maintain reasonable irrigation efficiency without causing deficit irrigation. Thus, W need estimates how much water would need to be diverted to optimally irrigate a field of alfalfa during the irrigation season. In addition to the IIS, a second irrigation scheme referred to as the Actual Irrigation Scheme (AIS) was introduced simultaneously to estimate the soil moisture conditions in an optimally irrigated field of alfalfa in which irrigation was limited to the period during which water was being diverted by each irrigation entity. Canal managers in these systems explained to us that they typically will not start diverting irrigation water until there is enough irrigation demand in the system to begin reasonably efficient deliveries. When a canal company starts ð3þ diverting water at the beginning of the season, there are usually significant seepage loses from the canal as the soil surrounding the canal system begins to saturate. Also during drought, irrigation may be delayed at the beginning of the season so that more water will be available during the high demand periods in the middle of the season. When water supplies are exhausted, the irrigation systems are shut down. In the Big Wood Canal Company and Salmon River Canal Company, during extreme droughts, canal deliveries have been shut down during the peak of the irrigation season after storage supplies were exhausted. An early shutdown of the canal system can result in significant soil moisture depletion at the end of the season. Therefore, in the coming year, water demand will be greater than predicted by the IIM due to the need to restore soil moisture caused by soil moisture depletion at the end of the previous season. In order to estimate antecedent soil moisture conditions caused by actual limitations in water availability, an interface between two different irrigation schemes is added to reset soil moisture condition at the beginning of the next season, so W need can account for antecedent soil moisture during the season-to-season transition. This transition was chosen to occur on January 1 for purposes of graphical analysis of model outputs, but this transfer of soil moisture could occur at any time outside of the irrigation season (November 16-March 14). Figure 3 shows the soil moisture transition between two irrigation schemes during Notice how the IIM maintains higher soil moisture than would be possible under actual conditions, because irrigations continue after the canal system is shut down. While it would be more accurate to calculate water demand for each tract using actual irrigated land and crop mix in a given season, to do so would then make the calculation of crop water need dependent on human management decisions which might be a response to drought. In diversion entities such as the SRCC, irrigators respond rapidly to changes in water supply through altering crop mix within the tract and adjusting the amount of land irrigated between seasons (Hoekema and Ryu, 2013). Efficient drought management causes these irrigators to reduce the seasonal water demand. Therefore, setting crop water need to that of uncut alfalfa guarantees that crop water need is driven by climate and not by management decisions. The use of uncut alfalfa as a reference crop is ideal since its crop water demand covers the entire growing season. It is the belief of the authors, through discussion with irrigators, that irrigators will try to set their crop mix so as to maximize water use during the entire irrigation season. The premise is that a failure to maximize water use ought to equate to a missed income opportunity. 744

9 CHARACTERIZING DROUGHT IN IRRIGATED AGRICULTURAL SYSTEMS: THE SURFACE WATER DELIVERY INDEX (SWDI) Comparison of the Duel Soil Moisture Model Applica on Irriga on Season by water right Soil moisture reset on Jan. 1 so that antecedent soil moisture condi ons are included in the ideal irriga on model Soil Moisture [mm] Precipita on [mm] 50 Canal opera ng Canal opera ng Precipita on Water Availability Irriga on Model Ideal Irriga on Model FIGURE 3. Soil Moisture as Represented in the Ideal Irrigation Scheme (IIS) and the Actual Irrigation Scheme (AIS) within the Salmon River Canal Company. The AIS provides an antecedent soil moisture condition on January 1st of each year for use in the IIS that is used to calculate W need. Water Demand Adjustment Factor (F) A water demand adjustment factor is needed for each irrigation entity. The water demand adjustment factor accounts, in part, for canal losses and crop mix variability between irrigation entities. This factor was established by adjusting F until SWDI equaled 1 at the 90th percentile of the annual diversion volume utilized over the 22-year period ( ). Hoekema and Sridhar (2011) established the canal diversions across the Snake River Plain increase as water supply increases, until a threshold is reached at which point diversions remain relatively constant while supply increases. In their study, water supply was represented by the SWSI. Once the adequate water supply threshold is passed, variability in the water demand from year to year must be mostly dependent on the variability in crop water demand due to the climatic conditions of the given year. Using the 90th percentile of annual diversions to establish F is meant to guarantee that water supply does not occur during periods of water limitation and is controlled by years with good water supply and high crop water demand. Using the 90th percentile allowed SWDI to approach a maximum value of 1.1 which would indicate in some years that over irrigation might occur, which seemed to be a reasonable assumption. It is assumed that as irrigation entities become more efficient their water demand may decrease. As a whole there is a well-documented decline in irrigation diversions in the Snake River Plain largely thought to be the result in improvements in delivery efficiencies, land use changes, and more efficient onfarm irrigation practices. In some cases long-term declining trends in diversions were observed. In order to account for declining diversions, long-term trends in land use change and crop mix SWDI was adjusted to remove trends by assuming that water demand should have been equally met in 1997 and 2011, which were years with high carry-over and unusually high natural flow. Natural flow is a calculated flow that estimates the amount of water that would have been in the river had reservoirs passed all flows during the year. The natural flow is the flow rate at which water rights are administered. This trend adjustment was only applied to the BWCC, NSCC, and TFCC because SWDI was found to be significantly less than 1 in 2011 for these entities and aerial photos confirm significant conversion into pivot irrigation within this period. RESULTS The Results section discusses the validity of the W need component of the SWDI, and then compares how shortfalls varied across the surface water entities during the drought years as identified by SWSI in the pertinent basins. 745

10 HOEKEMA AND RYU W need Validity The validity of the W need component of the SWDI as a measure of the normalized crop water demand can be seen by comparing historic diversions to predicted demand (i.e., W need ) during a period of years with relatively adequate water supply. In general, PDSI and SWSI indicate that there was limited drought in this region from 2005 to 2011 as shown in Table 2. The Pearson correlation coefficient, r, was used to quantify a relationship between predicted water demand, W need, and actual diversions, W diversion, for the limited drought period ( ) and the study period ( ). A correlation of more than 0.72 is achieved for all irrigation entities during the Limited Drought Period, except (as we shall see later) the most drought prone entities: SRCC, BWCC, AFRD2. Notice how the correlation in all entities declines between the Limited Drought Period and the Study Period (see Table 2). For the most drought prone entities, the correlation is found to be negative for the study period. The negative correlation can be explained by a general tendency that indicated crop water demand trends to be higher in drought years because drought years tend to have less springtime precipitation and generally higher summertime temperatures. Thus, a negative correlation is developed when demand increases, while the ability to meet that demand decreases during drought years. The only entity that was found to have almost no correlation between demand and diversions is AFRD2. This lack of response between crop demand and diversion can be explained by the long conveyance distance in AFRD2. Water for AFRD2 is diverted across 110 km of desert through a leaky canal to the place of use. The canal is estimated to TABLE 2. Pearson Correlation Coefficient between Predicted Demand and Supply in the SWDI for the A&B Irrigation District (A&B), American Falls Reservoir District #2 (AFRD2), Burley Irrigation District (BID), Big Wood Canal Company (BWCC), Minidoka Irrigation District (MID), Milner Irrigation District (Milner), North Side Canal Company (NSCC), Salmon River Canal Company (SRCC), and Twin Falls Canal Company (TFCC). Irrigation Entity Limited Drought Period Study Period A&B AFRD BID BWCC MID Milner NSCC SRCC TFCC lose about 77% of the water diverted at the headgates (Contor, 2010; IDWR, 2013). The long conveyance and high seepage rate make adjusting diversion rates to meet climatic demand nearly impossible. Nonetheless, as we will see in the following section, the SWDI appears to be a good indicator for predicting water deficits within AFRD2. SWDI Results SWDI results are shown in two formats: tabular in Table 3, and spatially in Figure 4. It should be noted that in the tabular data, PDSI is calculated for Climate Division 7, while in the spatial data, PDSI was downloaded from the WestWide Drought Tracker ( Table 3 identifies the percent of delivery for each irrigation entity as calculated by SWDI to the basin wide percent of adequate supply indicated by SWSI based on the agricultural supply threshold for the June SWSI. Note that in general, SWSI percent of supply follows a similar pattern and tends to be in the magnitude of the delivery percentage of the SWDI calculation. The June SWSI, July PDSI, and 12-month September SPI values for Climate Division 7, which represents the central Snake River Plain, are also shown in Table 3. The 12-month September SPI value captures precipitation from the beginning of the water year in October. Figure 3 which shows drought impacts in 2013, provides a good illustration of how dramatically drought impacts can vary between surface water irrigation entities. The PDSI for Climate Division 7 was 2.7 (moderate drought), and the SWDI for the Big Wood, Salmon Falls Creek, and Snake River were 2.7, 2.5, and 2.5, respectively, which represents a water supply percentile of 17-20% for the 34-year period of record currently used to calculate the SWDI value. Using USDM, percentiles of SWDI values would represent a moderate level of drought. During the 2013 drought SWDI indicates that the SRCC 54%, TFCC 83%, NSCC 89%, AFRD2 68%, MID 92%, BID 89%, A&B 88%, and Milner 85%. Thus, the drought impacts ranged from severe for the BWCC (using a provisional estimate) to no drought impacts for the MID. In 1991, PDSI (see Figure 5a) indicates a severe drought in the central Snake River Plain. However, at that time water supplies at the headwaters of the Snake were in good condition (carry-over and runoff were better than average). This is a classic situation where the climatic condition at the source and the point of delivery were dramatically different. While SWDI indicates that some demand was unmet by deliveries for AFRD2 and Milner ID, there were no 746

11 CHARACTERIZING DROUGHT IN IRRIGATED AGRICULTURAL SYSTEMS: THE SURFACE WATER DELIVERY INDEX (SWDI) TABLE 3. Comparison of the July PDSI and September 12-SPI for Climate Division 7; the SWSI for the Snake near Heise, SWSI for the Salmon Falls Creek, and the SWSI for the Big Wood River with Their Respective Shortfall in Supply to SWDI Values for the Nine Surface Water Irrigation Entities. The entities diverting from the Snake River are listed according to land area from the largest to the smallest. July PDSI September 12 SPI Snake SWSI Supply Deficit TFCC SWDI NSCC SWDI AFRD2 SWDI MID SWDI BID SWDI A&B SWDI Milner SWDI BW SWSI Deficit BW SWDI SF SWSI Deficit SF SWDI N/A

12 HOEKEMA AND RYU 2013 FIGURE 4. The 2013 SWDI Delivery Percentage Map for Central Idaho Underlain by a July PDSI Map from WestWide Drought Tracker. other shortages. However, the SWSI on Salmon Falls Creek and the Big Wood River indicated that water supplies were 50 and 62% of the adequate supply, respectively. SWDI indicated that the SRCC and the BWCC received 50 and 29% of the crop water demand, respectively. Both the SWSI and SWDI indicate an exceptional level of drought impact. The following year, in 1993 (Figure 5c), there was no drought in the central plain, but some water shortages lingered in AFRD2 and SRCC. Again in 1994 (Figure 5d), a similar condition existed as in 1991 (Figure 5a); there was severe drought in the central plain, but drought was less severe at the headwaters of the Snake River and carry-over from the previous year allowed for adequate water supplies. The most severe drought of the 1990s as indicated by each of the SWSIs and the PDSI occurred in 1992 (Figure 5b). Water deliveries on the Salmon Tract supplied only 19% of the demand, while only 15% of demand was met by the BWCC. Just below the BWCC, AFRD2 was able to divert water from the Snake River to meet 67% of the crop water demand. Outside of AFRD2, a moderate level of drought impacts was felt only for the large irrigation companies NSCC and TFCC. The other entities experienced little drought impact. A review of SWSI indicates that 1992 was a single drought year from the supply perspective. Interestingly, the year with the most significant drought impacts on the Snake River occurred in 2004 (Figure 5f) at the end of a four-year drought period that began in 2001 (Figure 5e). While 1992 (Figure 5b) and 2001 (Figure 5e) were the most severe droughts from a supply (SWSI) and climatic perspective (PDSI and SPI), they were not the years with greatest delivery shortages. Because multiple drought years had depleted the Snake River reservoir system in 2004, drought impacts reached severe levels within AFRD2. In 2004, 39% percent of the demand was met within BWCC, 54% of the demand was met within AFRD2 and the SRCC, 65% of the demand was met at Milner, and 75 and 80% were met within A&B and NSCC, respectively. Table 3 indicates that the BWCC, SRCC, and AFRD2 are much more prone to delivery shortages than the other irrigation entities, which during the study period only experienced moderate levels of FIGURE 5. Drought Characterization Using Gridded PDSI Values for Non-Surface-Irrigated Regions and SWDI to Illustrate the Delivery Shortfall for Nine Surface Water Irrigation Entities in the Years 1991, 1992, 1993, 1994, 2001, and The color scheme is based on the ratio of the demand met: (1) White SWDI >0.9, (2) Yellow SWDI , (3) Sand SWDI , (4) Orange SWDI , (5) Red SWDI , and (6) Dark Umber SWDI <

13 CHARACTERIZING DROUGHT IN IRRIGATED AGRICULTURAL SYSTEMS: THE SURFACE WATER DELIVERY INDEX (SWDI) (a) 1991 (b) 1992 (c) 1993 (d) 1994 (e) 2001 (f)