7

Drought Impacts, Impact Data, and Nonstationarity

This chapter focuses on drought impacts, explicitly defined as an indicator of the potentially harmful outcomes of drought. Drought impacts are highly variable between systems (e.g., ecological vs. hydrological) and communities (e.g., Indigenous peoples vs. municipal water users), and the current infrastructure for collecting, reporting, and assessing drought impacts similarly varies across regions, sectors, and drought types. Nonetheless, drought impacts are an essential element of drought assessment and are affected by nonstationarity both in the manifestation of the hazard itself and in societal and ecological changes shaped by dynamic vulnerabilities and adaptation decisions.

DROUGHT IMPACTS

Drought impacts are different from indicators and indices in important ways. Drought indicators are raw variables or parameters that describe a hydrometeorological state such as precipitation, temperature, soil moisture, streamflow, or groundwater level. By comparison, in environmental contexts, an impact is the direct or indirect effect that a hazard or disaster has on a particular system, place, or people and culture (Lindell, 2013). This can include damage or destruction to property, livelihoods, and environments, and can reflect a reduction in the capacity for people—individuals, families, and communities—to maintain their standard of living and mental or physical health (Lackstrom et al., 2014). In drought, an impact extends beyond the social world to include effects on the health of landscapes, species, and ecosystem services. Impacts reflect the susceptibility to or actual harm from drought to a specific system and can be modulated by its onset, severity, duration, and mitigation efforts. An impact, then, is an expression of exposure combined with the adaptive capacity of an individual, group, or system to mitigate drought that results in harm to the system of interest (Lackstrom et al., 2013). An indicator of drought on a river system, for example, might include

reduced river flows, while an impact to a river system might be fish kills or municipal water restrictions that result from reduced river flows. A system of structures, networks, and regulations (e.g., dam releases or recreation closures), however, might intervene in a drought to reduce damage to riparian areas, support fish and other species, and insulate downstream agriculture and tourism industries from economic losses. Impacts, then, are an important indicator of harm within the complex interaction of the hazard, exposure, and adaptive capacity of a system when affected by drought. For this report, the committee has adopted the following definition for drought impacts:

For further clarity, Figure 7-1 provides examples of indicators, indices, and impacts for different drought types. Following this framework, unusually dry soil or low stream levels are not, by themselves, drought impacts, but instead are indicators of potential drought conditions. In these situations, indices would be statistical representations of the drought severity and/or rarity such as the Soil Moisture Volatility Index (Osman et al., 2024) or a streamflow percentile. Impacts in these cases would be, for example, the deleterious effect of dry soils on crop yields or fish kills caused by low stream levels.

Drought impacts also serve other functions. Impacts inform drought products like the U.S. Drought Monitor (USDM) and have been used for decades to calibrate and validate numerical and physical drought models, including the Palmer Drought Severity Index. In this way, drought impacts can act as user knowledge as an expert heuristic to benchmark geophysical and numerical drought indices. Through a combination of scientific and on-the-ground observations, impacts can be combined to reflect a snapshot of a current or ongoing drought, which may help communities understand the environmental and societal effects of a drought (Lackstrom et al., 2017). Importantly, many governmental and policy entities use impacts as a trigger to determine what resources are needed and for whom (e.g., pasture damage triggering open haying in state-owned lands or deer disease and kills triggering a reduction in hunting tags made available). Impacts may likewise point to gaps in observation and monitoring systems that might otherwise permit individuals, groups, and organizations or agencies to employ mitigation strategies to enable future adaptive capacity.

Conclusion 7-1: Impacts are complicated manifestations of drought, but they are nonetheless critical to the entire drought assessment process.

Drought Impacts: Stakeholder Perspectives

For those who have lived in a particular place for generations and have developed a deep relationship with it, drought impacts are more than indicators in a hazard cycle. Impacts can reflect the overall health of peoples’ relationship with their ecosystem, including misalignments between them. Perception of impact magnitude can also signify

people’s calibration to long-term experience of “normal,” which can manifest with descriptors like “worst I’ve ever seen.” This is certainly true for Tribal peoples whose identity and culture are tied to place. But it can also be true for agricultural producers who depend upon the orderly coming and going of seasons for their livelihoods. Water managers, ecologists, and natural resource managers may be more able than Tribes and agricultural producers to set aside drought impacts when they go home at the end of the workday, but drought nonetheless affects them.

Tribes

For Tribes, Native Hawaiians, and Alaskan Natives, drought impacts may be best understood in the context of an approach to the environment embodied not by traditional Western scientific practices but by knowledge systems like Traditional Ecological Knowledge, or TEK, which is characterized by a comprehensive and integrative approach to human and natural systems. Indigenous peoples who have inhabited regions of the United States for centuries, for example, have developed long-term observations of past social-ecological interactions and often reveal important insights into changes in species diversity, ecological processes, land management outcomes, and public health. Importantly, although characterized in traditional scientific narratives as subjective, TEK holds significant value in its deep-time perspective, which as many studies have detailed, “may be leveraged to define baseline conditions, establish restoration targets,

track global change impacts, and serve as an early warning system of large-scale ecological state transitions” (Souther et al., 2023). Incorporating TEK and related perspectives may allow drought assessment frameworks to become more useful and usable to Tribes and Native communities, integrating them into their lived experiences with drought. Such frameworks may likewise expand timelines for early drought detection and reshape the nature of impacts that are collected to include more indirect impacts (e.g., mental or public health) or impacts that are difficult to measure (e.g., community relationships with the ecosystem). The National Integrated Drought Information System (NIDIS) Tribal Drought Engagement Strategy 2021–2025 (Bamford et al., 2020) documents collaborative work between NIDIS and Tribes in the Missouri River Basin and Midwest in support of enhanced and inclusive drought early warning.

Agricultural Producers

When drought limits water availability, crops suffer from reduced plant growth, yields, and crop quality. Rainfed agriculture is affected through reduced precipitation. Irrigated agriculture is affected if drought reduces snowpack, streamflow, or groundwater recharge, all of which can prevent replenishment of stored water supplies. In rangeland livestock systems, drought reduces summer forage availability, as well as yields of the irrigated hay crops that are often required to feed livestock over the winter months when forage resources are not available due to harsh weather conditions. These drought impacts reduce farm/ranch income, which in turn can affect the broader economy in rural, agriculture-dependent communities through reduced harvest and processing activities and reduced spending by directly affected farm/ranch households.

A dry year creates uncertainty for agricultural producers. A row crop farmer wonders whether crop sales will be enough to cover the operating loan they received from the bank at the start of the growing season. A rancher wonders whether their livestock will gain enough weight grazing on rangelands with reduced grass availability. They also wonder whether the lower yields on their alfalfa and other hay crops will lead to a feed deficit for their livestock over the harsh winter months; and if so, how far they will have to travel (and pay) to purchase replacement hay. These impacts can cascade to increased food prices, possibly resulting in increased food insecurity locally and nationally.

If the drought is severe, the farmer wonders whether the negative impacts of drought will be enough to trigger federal financial assistance to help them manage their losses. The livestock producer wonders whether they need to sell cows whose genetics they may have spent years refining, even though rebuilding the herd in the future will be expensive. In the Western United States especially, these agricultural producers also observe the drier grass and feel the dust around them, which increases their stress around heightened wildfire risk. An agricultural producer may be able to weather a drought year, but two or three such years will begin to wear on their financial reserves and their mental health (Yazd et al., 2019; Linder et al., 2025). Such strain on producers can have indirect impacts, such as negative mental health outcomes (OBrien et al., 2014), especially for those in rural areas.

Water Resource Managers

Water managers at municipal utilities and other public water supply systems are responsible for supply, treatment, and distribution of water to their customers. The built infrastructure facilities that they operate (reservoirs, canals, drinking water, and wastewater treatment) allow them to manage a certain level of variability in year-to-year water supply availability and customer water needs. When drought lasts longer or is more severe than the built infrastructure was designed for, drought impacts begin to emerge. Water managers may need to impose frequent water use restrictions that inconvenience their customers or consider cost decisions such as leasing agricultural water for short-term response. In more extreme cases, communities may experience shortfalls that threaten human health. Reduced streamflow may increase water temperature, creating challenges for nuclear and thermal power plants that rely on water to cool plant reactors. Reduced streamflow can also lead to water quality impairment in wastewater treatment systems that rely on high dilution. Drought may also harden the soil, preventing infiltration and leading to greater runoff and flood risk.

Natural Resource Managers

Reductions in water flow and volume in rivers, streams, and lakes can lead to habitat fragmentation and biodiversity loss. Wetlands can diminish in size, reducing habitat for numerous aquatic species, amphibians, and migratory birds. Normal migration patterns of aquatic and terrestrial species can be disrupted. Water quality is also often compromised by drought. Decreases in water flow and volume can lead to higher water temperatures and increases in algal production. Pollution present in water bodies is also less easily diluted when water flows and volume are low (Mosley, 2015). Especially during prolonged periods of drought, threats to natural systems from drought can be exacerbated by increased extractions for agricultural and municipal water uses.

Conservation policies to protect plant and animal species have generally been designed for a stable climate, yet climate change is shifting habitat and growing conditions. Protected areas may no longer support the plant and animal species for which they were established. Plants may shift their range, and animal species that have historically been protected may move to new areas that lack legal protections, in search of water or more desirable climate conditions. Wildlife may find their migration patterns disrupted in time or space, whether by drying wetlands, wildfire, or shifting timing in food source availability. Further, wildlife and natural resource managers can find ecosystem restoration more challenging when historical conditions are no longer attainable due to climate change. Ecosystem transformation has emerged in recent decades to support healthy and productive ecosystems in the face of significant climate and environmental change (Jackson, 2021). Natural resource managers are confronted with myriad decisions in this process, many under deep uncertainty and resource limitations (Crausbay et al., 2022). From these significant challenges have risen multiple, effective frameworks for guiding natural resource management decisions toward ecological transformation. One of the most prominent is the resist-accept-direct (RAD) framework (Schuurman et al., 2020), which characterizes decisions on a spectrum between the categories of resisting change, accepting change, and directing change.

RISK FRAMEWORK FOR IMPACTS

Drought impacts, by their very nature, are partly determined by humans and human actions. Returning to the risk-informed drought assessment framework introduced in Chapter 1, the risk of a drought impact can be framed as an interaction among the drought hazard and the system’s exposure and adaptive capacity. The drought hazard is a physical meteorological or hydrological process described in previous report chapters, and drought is often characterized with indicators and indices. Agricultural, water resource, cultural and social, and economic or market systems exposure and adaptive capacity are human constructs, and are largely determined by decisions in policy, planning, and engineering. For example, the same meteorological conditions (i.e., the hazard) could elicit a significant drought impact for an undersized or outdated water supply system compared to an adequately sized system (i.e., the exposure or adaptive capacity). In this case, the relationship between a geophysical indicator, like precipitation anomalies, and a drought impact will be very different between the two water systems because of the systems’ different exposures and adaptive capacities. For ecological systems, exposure and adaptive capacity can be complex mixes of human and nonhuman constructs that can be determined by decisions in policy, planning, and management, but are also determined by nonhuman factors such as biodiversity, ecological synergies, and species-level disturbance and stress resilience (Crausbay et al., 2022). It is therefore critical that advances in drought impact reporting and data collection account for the inherent dependence of impacts on exposure and adaptive capacity from both human and nonhuman causes.

Conclusion 7-2: System exposure and adaptive capacity are important parts of the risk of drought impacts, and changes in either can affect the likelihood and/or severity of a drought impact. Therefore, along with drought impact data, drought assessment should regularly collect and report information on changes in a system’s drought exposure and/or adaptive capacity.

Risk-informed drought decision-making relies on drought impact information to understand current conditions but also relies on documented drought hazard-impact relationships to predict potential future impacts for both emergency management and long-term planning applications. The risk of a drought impact can change with an increase or decrease in a system’s exposure and/or adaptive capacity, irrespective of any changes in the drought hazard (examples include growing human demand for water resources, ecological shifts that increase disturbance impacts, and others described in Ashraf et al., 2021; Hadley et al., 2021; Rodíguez-Flores et al., 2023; Coder et al., 2025). Therefore, drought assessment frameworks need to be proactive in updating system-specific attributes of exposure and adaptive capacity so that they can properly assess, forewarn, and communicate the potential of a drought impact corresponding with a particular drought hazard. For example, if a water supply reservoir increases its storage capacity through expansion or dredging, it may increase its adaptive capacity to drought and therefore decrease the risk of a water supply drought impact. This

information on changes in system exposure and/or adaptative capacity are equally important to document and communicate as changes in a drought hazard itself. Local and state governments and agencies can address this challenge of estimating drought impact risk via changes in exposure and/or adaptive capacity through regular and robust data collection including public and commercial water use, water resource health assessments, and ecosystem drought resilience assessments, as well as through planning such as regional water supply planning, hazard mitigation planning, and stress-test and tabletop drought exercises.

Conclusion 7-3: Assessment of drought impacts requires information on drought conditions as well as the status and adaptive capacity of affected systems to inform operational drought response and long-term planning, but mechanisms for collecting and using such data do not exist consistently across the United States. State government agencies (e.g., natural resource, agriculture, and environmental protection agencies) in collaboration with local governments may be best positioned to undertake collection of data and planning that are relevant to drought exposure (e.g., water use, stream gauge, and low flow measurements) and adaptive capacity across systems (e.g., through water supply and hazard mitigation plans) and use of that information to reduce drought impact risk (e.g., tabletop exercises of existing drought plans).

DROUGHT IMPACT DATA, COLLECTION, AND REPORTING

Drought impact information is widely used for local- and state-level drought assessment, including triggering specific mitigative actions. For example, the Missouri Drought Mitigation and Response Plan uses drought indicators and indices to determine the state’s drought phase and to scope potential mitigative actions; however, the plan uses drought impacts to determine which mitigative actions should be enacted (Missouri DNR, 2023). Drought impact data are also used to establish relationships with geophysical indicators such as precipitation anomalies and indices like the Palmer Drought Severity Index. Strong and reliable relationships between drought indicators and impacts are necessary to effectively predict, forewarn, and assess drought impacts in a systematic and scientifically robust way. The connection between physical drought indicators and their societal and ecological consequences is neither automatic nor uniform across regions and sectors. Traditional drought monitoring has focused primarily on physical anomalies, with limited systematic documentation of impacts. This gap impedes calibration of monitoring systems to real-world relevance and obscures understanding of which physical conditions translate into which types and magnitudes of consequences (Enenkel et al., 2020).

Many peer-reviewed studies over the past few decades (see, e.g., Bachmair et al., 2015; Stagge et al., 2015a; Parsons et al., 2019; Kchouk et al., 2022) have worked to establish relationships between drought indicators and impacts with varying levels of success. However, innovation in drought impact prediction and assessment with more easily measurable and quantifying indicators has been impeded by the continued lack

of systematic and holistic drought impact data collection and cultivation. Advances in artificial intelligence (AI) and machine learning and participatory design in recent years have greatly improved the collection, usability, and actionability of drought impact data and the incorporation of expert knowledge. Large language models, in particular, have shown promising benefits in more exhaustively collecting and synthesizing drought impact information (Shang et al., 2025; Wang et al., 2025), which could help fill in significant impact information gaps to improve all phases of drought assessment. However, continued work is needed by the entire drought impact community to expand and standardize impact collection so that drought assessment activities are grounded in accurate and representative drought impact information.

Drought Impact Data

Drought impact data are invaluable for all parts of drought assessment and are necessary to understand and predict relationships between geophysical indicators and social, economic, and environmental repercussions of drought. However, the diversity and complexity of drought impacts, even within one geographic region, have impeded the development of a systematic framework by which impacts can be easily and consistently integrated in drought assessment. Nevertheless, impact data have been an important component of drought assessment in the United States for decades. Drought impact information is collected by state, local, and Tribal scientists and officials through regular contact with individuals and groups representing public and private sectors that are affected by drought.

The diversity of drought impact reporting capacity, responsibility, and interest between state, Tribal, and federal entities has created a complex patchwork of drought impact reporting pipelines, which has resulted in some states or sectors having more efficient and effective drought impact reporting than others. The myriad drought impacts are reported to different organizations, including University Extension and state departments and agencies. Some local-level federal offices such as the Natural Resource Conservation Service and Farm Service Agency have collected drought impact information; however, this effort has largely been the individual offices’ decision without a task from the federal U.S. Department of Agriculture (USDA). Each of these organizations has different ways of collecting, reporting, and using the impact information, often with varying degrees of documentation and protocol. Some entities have developed systems to facilitate effective drought impact data collection, including web-based tools for individuals and organizations to report drought impacts. For example, Montana developed a statewide drought impact reporting system to streamline the impact data collection process and to better inform drought decision-making. The National Drought Mitigation Center (NDMC) has similarly developed a nationwide tool for drought impact and condition reporting, the Condition Monitoring Observer Reports on drought (CMOR, Smith et al., 2021) tool. While drought impact data largely remain much more inconsistent and disorganized, CMOR and state-level impact data collection services have improved impact information flow into drought assessment in recent years. Similarly, citizen science initiatives, such as the Community Collaborative Rain, Hail, and Snow

(CoCoRaHS) network have grown self-reported drought impact systems that have greatly benefited drought monitoring and post-event assessment (Lackstrom et al., 2017)

Agricultural impacts of drought arguably have the most refined and systematic impact data collection frameworks in the United States, largely facilitated by USDA. Agricultural impacts, such as disrupted or delayed field work, stunted crop growth, elevated irrigation demands, poor pasture conditions, and decreased yields, are reported by agriculture special interest organizations such as state farm bureaus and crop associations. Weekly crop and soil condition and progress have been regularly reported during growing seasons for several decades, in a reliable and accessible format that permits relatively easy drought assessment and scientific research. Equally reliable annual reports of indemnity payments by federal government programs have similarly facilitated advancements in the understanding of the socioeconomic impacts of agricultural drought on high-value crops and production systems across the United States.

Impacts to water resources and other hydrological data collection and cultivation are often available for use in drought assessment. Drought impacts to hydrology and water resources are tracked and data are collected by federal, state, Tribal, and local governments as well as by semiprivate or private water management groups, and private citizens. For example, drought impacts to public supply water reservoir levels may be reported by the Army Corps of Engineers, one of many state agencies, or local municipalities, depending on the ownership and management of the water body. In these cases, the regular stream stage or reservoir level data collected and reported by federal or state governments must be married to the stage or level at which an impact may occur (such as reduced water intake capacity for potable water supply) to predict, forewarn, or assess the hydrological drought impact. The U.S. Geological Survey and National Oceanic and Atmospheric Administration, in collaboration with state agencies and local governments, have taken great strides in standardizing this important surface water resource impact information to help guide management decisions and actions; however, more work and coordination are needed to improve the reliability and actionability of hydrological drought impact information. Furthermore, human-induced changes in water demand or supply in surface water systems can reduce the predictability of water supply impacts from drought, and therefore the indicator-impact relationships must be regularly updated.

The inconsistent relationships between geophysical variables and hydrological or water resource drought impacts are even more complex for groundwater systems. Both unconfined and confined aquifer systems can be affected by drought through reduced recharge and increased water demand and dewatering. However, groundwater monitoring, modeling, and projection are challenged by a significant lack of measurements and geologic characterization coupled with rapid changes in water demand. The underlying geology largely determines the groundwater recharge rates following significant drought, and this information is difficult to obtain at the spatial scales needed for accurate water supply planning in groundwater-dependent regions. Furthermore, the longer timescales of groundwater drought response and recovery relative to the more rapid responses for agricultural and surface water responses and recovery can

challenge traditional drought assessment systems and indicators. Recent and continued advances in large-scale groundwater resource monitoring via remote sensing, combined with more efficient AI-assisted modeling and advanced physics-based modeling, have the potential to greatly expand the ability to assess groundwater resources and their response to drought. It is important for drought assessment frameworks to develop the flexibility to incorporate the growing wealth of groundwater information as these innovations continue.

Private industries can also be an important source of drought impact information. Examples include reports from energy and power generation companies affected by reductions in power production from surface water-cooled power plants, transportation and logistics companies affected by reduced maritime traffic due to restrictively low river levels, and insurance and reinsurance companies affected by increased damage claims from crop loss or fire damages.

Ecological impact data collection is arguably the least well developed in the United States. This is partly due to the relatively recent acknowledgment of ecological drought as an important form of drought that is separate from agricultural drought, the complexity and varied timescales of ecological response to and recovery from drought, and the relatively indirect economic and social impacts and mitigation of ecological drought. Natural resource impacts, including to aquatic and terrestrial ecology, are reported by scientists and natural resource managers, as well as by recreation and outdoor enthusiasts. Ecosystem health and species collections are two examples of critical ecological drought impact data and are often collected by federal agencies such as the U.S. Forest Service and National Park Service, various state agencies, Tribal experts, local government units (e.g., forest preserves), university and nonprofit organization scientists, and private citizens. These data are critical for post-event drought assessment and scientific research on ecosystem drought vulnerability, as well for informing ecosystem management and adaptation decisions from local to federal scales.

One of the strengths of ecological drought information is the long legacy of species data collection across the United States, in some cases dating back centuries (Bellew and Boudreau, 2025). These records, while sometimes inconsistent, allow scientists to establish drought-ecosystem relationships that can transcend the multidecadal internal variability of the climate system, and establish a robust record of long-term change in ecological composition and health (Rocha-Ortega et al., 2021). Additionally, ecological information, such as tree rings and fire scars, provide useful information for regional drought risk assessment that spans farther into the past than any direct weather observations. However, there remain significant gaps in actionable ecological drought impact data. Remote sensing has helped reduce this information gap by providing virtually real-time indications of ecosystem response to environmental conditions; however, more work is needed to better establish reliable triggers and thresholds directly corresponding to drought impacts across different ecosystems and to support effective ecological transformation. These research and data needs are arguably greatest in the nation’s most heterogeneous ecosystems: urban areas. Drought can have significant impacts on urban ecology, including reducing ecosystem services of green infrastructure such as

tree cooling potential. The plethora of microscale environments and inconsistent human intervention in urban areas limit the potential usability of traditional remote sensing tools for ecological drought impact information collection. One advantage of urban environments is the high density of potential reporting sources. Advancements in citizen science ecological monitoring and reporting, in particular, have helped fill gaps in urban ecological drought monitoring, and these citizen reports have been used in recent urban drought assessments (e.g., Lackstrom et al., 2017; Brown and Williams, 2019).

Other Approaches to Collecting Impact Data

Recent initiatives have begun to address this deficit of impact data through systematic impact documentation. The European Drought Impact Report Inventory, containing nearly 5,000 impact reports from 33 countries, reveals the same prioritization of agricultural and public water supply impact reports, which dominate documented drought consequences (Stahl et al., 2016). The National Drought Mitigation Center’s Drought Impact Reporter has similarly collected impact information from traditional and social media, government and private sector statements, citizen science initiatives and other sources, and provides these reports in a consistent and easily accessible format (Smith et al., 2014). Global assessments using geocoded disaster databases demonstrate that correlations between physical drought indicators and reported impacts vary by region and impact type, with hazard metrics derived from land reanalysis showing stronger relationships in some contexts than others (Kageyama and Sawada, 2022).

Emerging methods for automated extraction of impact information from social and news media offer potential for near-real-time impact monitoring at unprecedented spatial and temporal resolution (Shang et al., 2024). The Social Drought dataset, comprising over 1.5 million social media posts aligned with expert-verified news articles and USDM classifications, demonstrates proof of concept for integrating conventional meteorological data with unconventional social media signals to provide holistic understanding of drought impacts. However, significant challenges related to data quality, representativeness, algorithmic bias, and interpretation remain before such approaches can be operationally integrated (Shang et al., 2024). While recent advances have been made in the collection of drought impacts from social and traditional media, including through crowd-sourcing, there has been relatively little advancement in the ability to process, interpret, and communicate these huge datasets to support effective drought decision-making.

The operational value of impact data extends beyond validation of physical monitoring systems. When drought severity classifications can be explicitly linked to impact thresholds, decision-makers can establish consistent triggers for interventions, allocate resources based on demonstrated need, and communicate risk in terms that resonate with affected populations (Stahl et al., 2016). The drought classification scheme presented in Table 6-1, while defined on a standardized statistical scale, gains operational meaning through calibration against observed impacts in specific sectors and regions.

Conclusion 7-4: The growing wealth of drought impact information presents an opportunity to improve drought assessment at national, state, and local levels, especially as innovations and AI and other technology and science continue to be developed.

Recommendation 7-1: NIDIS should work with decision-makers, scientists, and the broader drought community to develop a set of best practices by which drought impacts data can be consistently and effectively used for all aspects of drought assessment, especially for state drought plans and other policy and action plans.

Drought Impact Data Collection and Use

Drought impacts are used both for internal state and local government decision-making and to inform nationwide drought monitoring and mitigation efforts. State agencies and organizations, including state climate offices, collect drought impact information through regular and sometimes mandated contact with local governments and agencies as well as private citizens. The information may be regularly collected irrespective of drought conditions or may only be collected and communicated when drought is recognized by the state. Many states have integrated drought impact collection and data into their drought preparedness and mitigation plans, and these plans have linked specific policy or regulatory actions to impacts. Similarly, local governments and decision-makers often look to drought impacts to inform mitigative actions, including water conservation measures and burn bans.

Drought impact data are also used by private industries and can sometimes significantly affect economic markets. This is especially the case with agricultural drought impact data, including crop progress and yield information that are regularly collected and reported by USDA. Agricultural drought impacts are also critical for traditional (i.e., not parametric) insurance programs offered by state and federal governments and by private insurers. Because drought often reduces on-farm income, these programs are vital for agricultural production and profitability during and following drought years.

U.S. Drought Monitor

The USDM incorporates objective drought indices and indicators based on geophysical data as well as drought impacts information. The drought indices and indicators are based on historical data that have been converted into a percentile format that is directly relatable to the USDM Dx categories and are available every week nationwide; they are the primary tool used to determine the Dx status. However, the drought impacts data are not provided on a consistent weekly basis for all states and do not have the required historical record for conversion into a percentile format; consequently, they cannot be consistently incorporated in the same way drought indices and indicators are and must be evaluated based on local expert knowledge.

USDM authors use drought impact reports two ways. The first is to highlight areas that need to be examined in more detail with objective indicators. This typically happens

when an area is not yet in a drought or abnormally dry status but is experiencing stress as indicated by the impact information, likely due to developing flash drought (for flash drought, impacts frequently lead the indicators). The second way is to refine a Dx status when the objective drought indices and indicators yield different signals (i.e., for different timescales [e.g., long-term vs. short-term], different sectors [e.g., agricultural vs. hydrological], or different products [e.g., soil moisture derived from in situ observations, remote sensing, and/or models]).

The key to the USDM methodology is the convergence-of-evidence approach. Ideally, the decision to assign a Dx status is dependent on the various objective drought indices and indicators “converging” to a particular drought state. This is also true for drought impacts information. In most cases, the impacts that are being experienced should be consistent with what the indices and indicators are saying (the exception being flash drought as noted above).

Impacts information is being collected and summarized by NDMC and CMOR, but better, more comprehensive, and standardized impacts reporting is needed: impacts information across a spectrum (e.g., when it is dry, when it is wet, and in between) and context (e.g., does it always look this dry in July, or is it an anomaly?).

Conclusion 7-5: The current infrastructure for collecting and communicating drought impacts is inadequate and impact data are not collected evenly across drought impact types (e.g., less actionable impact information for ecological drought), which has created uneven emphasis for drought assessment and response on some systems (e.g., agriculture) over other systems (e.g., wetlands) that are impacted by drought.

Recommendation 7-2: NIDIS should facilitate the development or improvement of systems for systematic collection, reporting, and integration of drought impacts consistently across sectors, regions, and interests, for multiple uses, including drought assessment, adaptation, and other decision-making. In this work, NIDIS should collaborate with the USDA (agriculture and forest), Department of Interior (coastal, ecological, water resources), Department of Homeland Security (drought response/resilience, national security), Bureau of Land Management (fire, rangeland), Health and Human Services (public health), Environmental Protection Agency (water resources, air and water quality), and Tribal communities, as well as the broader drought community.

INCORPORATING IMPACT DATA INTO DROUGHT ASSESSMENT

Impact data are already incorporated in most aspects of drought assessment. However, the process by which this is done is inconsistent across states, regions, sectors, and drought events. Even within the USDM, impact data are not provided consistently in time or space, which forces the author to determine whether and how they will use the patchwork of drought impact reports and data available. Furthermore, the current disorganized system of drought impact data cultivation impedes scientific understanding

of relationships between drought indicators and impacts and effective prediction, early warning, and communication of those impacts. Therefore, proper incorporation of impact data into drought assessment requires expansion and improvement of systematic drought impact reporting across systems, regions, and interests. The required attributes of such a drought impact reporting system include (1) sufficient impact report frequency and spatial resolution for prediction, early warning, monitoring, and (ideally) impact mitigation; (2) sufficient timescales and periods of record to establish robust and reliable relationships between drought indicators and impacts; (3) dedicated and well-resourced groups of reporters and data collectors across the country; and (4) an entity or entities that can lead the facilitation of a nationwide drought impact data system. It is expected that the specific details of these four attributes will differ between drought types (e.g., surface water resources vs. forest ecology); however, all four attributes are necessary for successful incorporation of drought impact data into assessment (see Figure 7-2).

USDA’s National Agricultural Statistics Service (NASS) provides a good example of this type of impact reporting system. NASS is in ongoing contact with USDA local and regional offices, Cooperative Extension, state agriculture agencies, and individual farmers and producers, and they use this engagement to regularly collect information on crop and livestock progress, condition, and production. This system has most of the necessary attributes for drought impact data reporting and incorporation, namely that crop conditions and yields are reported at sufficient time intervals for both drought monitoring and post-event assessment; the impacts are recorded at either the county or state level (which is often sufficient for agricultural drought assessment); and there is a long record of impact data stretching back decades in most places. The data are also easily available and accessible for all aspects of drought assessment. These attributes are present because USDA has been able to develop and sustain relationships with individuals and groups who are reporting and collecting impact information, and because USDA has had support to establish and maintain this impact data collection infrastructure.

While the USDA NASS data and reporting system is far from perfect, it is an example of a successful means of systematically and consistently collecting and cultivating impact data for drought assessment and can serve as a general model with which to develop similar drought impact reporting systems for other sectors and drought types. Another example of interagency collaboration toward a broader goal of hazard mitigation is the National Interagency Coordination Center,¹ which coordinates resources and support for wildland fire across the United States. Whether ecological impacts, water resource impacts, or nonagricultural economic impacts, effective drought impact reporting and data systems must have each of the four attributes listed: timescale, spatial scale, reporters and collectors, and system facilitators (see Figure 7-2). Following this blueprint, drought impact collection, reporting, and data cultivation can be more easily standardized and compared across drought events and geographic regions and can more easily facilitate science research advancements in drought prediction, early warning, and monitoring.

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¹ https://www.nifc.gov/nicc accessed May 23, 2026.

Conclusion 7-6: Current drought impact reporting systems do not capture consistent or comprehensive drought impact information across time, geography, or drought types, which limits the usefulness of impact data to drought assessment and decision-making.

Nonstationarity

Drought impacts are strongly determined by the drought hazard and the exposure and adaptive capacity of the system of interest. All three of these components of drought impact risk can experience nonstationarity in both time and space. Therefore, drought assessment that explicitly uses impact data must account for nonstationarity in the geophysical hazard and or indicator used to characterize drought, and any potential nonstationarity in the exposure or adaptive capacity of the system of interest. Nonstationarity or changes in human practices that alter either a system’s exposure or adaptive capacity change the drought-impact relationship and therefore the underlying risk of a drought impact, which is one aspect of anthropogenic drought (AghaKouchak et al., 2021). Similarly, drought can cause long-term changes in ecosystem structure and function, which themselves affect the exposure and adaptive capacity of the ecosystem (Müller

and Bahn, 2022). Changes in the drought hazard or a system’s exposure or adaptive capacity can also elicit new or newly discovered drought impacts, such as vector-borne diseases like Dengue (Lowe et al., 2021) and West Nile virus (Erazo et al., 2024), which have been linked to drought and hydroclimatic variability.

Just as emerging or newly discovered drought impacts can be an effect of nonstationarity, so, too, can changes in the characteristics of more familiar impacts, such as impacts to agricultural production and electricity generation. For example, based on observed nonstationarity in agricultural loss data, some analyses have recommended that federal crop insurance programs adopt shorter loss histories for setting premiums while using longer time series to capture extreme events (Coble et al., 2011). Similarly, in its 2022 Integrated Resource Plan, the Pacific Gas and Electric Company moved from using a 30-year historical average of hydroelectric generation conditions to a 15-year average for which the impacts of climate change are more apparent (PG&E, 2022).

An ideal drought impact collection and reporting system should be flexible enough to respond to new or newly realized impacts and emerging threats.

Conclusion 7-7: Changes in human and nonhuman systems create nonstationarity in drought impacts and can change the impact-indicator relationship.

Conclusion 7-8: Drought impact collection and reporting systems need flexibility to respond to new or newly realized impacts and emerging threats.