Natural Resources Conservation Service Research Articles

The significance of basin slope for curve number estimation and the impact on flood prediction in arid basins

ABSTRACT The Natural Resources Conservation Service Curve Number (NRCS-CN) method was developed in agricultural basins with slopes less than or equal to 5%. This research investigates the relationship between the basin slope and runoff depth in arid basins by the NRCS-CN method. The results show that there is a clear effect of the proposed curve number equation with slope (the slope adjusted CN, CN IIα ) on the runoff depth in the studied basins, and this is consistent with the literature. However, large basin areas with a high percentage of alluvium area and vegetation, and high infiltration rates, counteract the slope of the basin, and consequently the basin slope will not have a significant effect on runoff. The correlation coefficient of various developed equations varies between 0.89 and 0.93 and the root mean square error of runoff depth varies between 11 mm for λ = 0.2 and 5.2 mm for λ = 0.01.

Greater sage‐grouse chick mortality risk relative to livestock grazing management, environmental factors, and morphometric measurements

AbstractGreater sage‐grouse (Centrocercus urophasianus; sage‐grouse) populations in the western United States have declined, necessitating conservation efforts. The United States Department of Agriculture Natural Resources Conservation Service and livestock producers implemented the Sage Grouse Initiative (SGI) to improve sage‐grouse habitat using regional‐specific management actions such as rotational grazing. We assessed the effect of SGI grazing management, the influence of brood female and chick morphometric traits, and multiple environmental and anthropogenic disturbance factors on chick mortality risk in a sage‐grouse population in central Montana, USA, from 2011–2019. We used a Kaplan‐Meier survival function to evaluate chick survival, Cox proportional hazards models to evaluate chick mortality risk as a function of brood female and chick morphometric traits, and the Andersen‐Gill formulation of the Cox proportional hazards model to assess the effects of time‐dependent habitat characteristics on chick mortality risk. Survival to 45 days post‐hatch for 510 chicks varied annually from 0.26 ± 0.07 (SE) to 0.69 ± 0.07. The 45‐day survival rate for all years combined was 0.51 ± 0.03. Chick mortality risk was not affected by changes in livestock grazing management implemented through the SGI grazing program. Brood female age and body condition, sex of chicks, vegetation, and anthropogenic variables were also unassociated with chick mortality risk. There were small protective effects of chick mass adjusted for age and mean minimum monthly temperature; greater chick mass and lower monthly temperatures correlated with reduced mortality risk. Overall, our study suggests the SGI grazing program does not confer additional benefits to sage‐grouse chicks beyond existing grazing practices. Incentivizing grazing practices that adhere to fundamental principles of rangeland ecology and maintain intact rangelands may be more effective than specific prescribed grazing systems for sage‐grouse conservation in this region.

Landscape changes and watershed erosion in Prince George's County, Maryland

AbstractThis study evaluated erosion rates and sediment production in streams, and factors potentially influencing them throughout the Anacostia, Patuxent, and Potomac (non‐Anacostia) River watersheds within Prince George's County, Maryland, US. As part of the County's watershed‐scale biological monitoring program, from approx. 1999 to 2008, permanent monuments were established to allow measurement of stream channel cross‐sectional (XS) area. The intent of this study was to characterize the intensity and spatial distribution of fluvial geomorphic instability across the county and use the results to target and plan stormwater management and stream restoration actions. For this study, 78 stream locations were re‐surveyed in 2020, representing a time lapse of from 12 to 21 years. Data collected included XS dimensions, modified Wolman 100‐particle pebble counts, and reach‐specific soil bulk density. Land use/land cover data were compiled from the National Land Cover Dataset (NLCD), precipitation from the National Weather Service Center for Environmental Information (NCEI), and soils from the Natural Resources Conservation Service Web Soil Survey (NRCS/WSS). We calculated percent change in XS area, rates of erosion, sediment yield, and assigned geomorphic classifications, and interpreted them in the context of spatial positions relative to changes in land cover characteristics. Sediment yields among the 78 reaches exhibited a combination of those undergoing enlargement/erosion (67.9%), reduction/deposition (25.6%), and the remaining 6.4% with essentially no change over the period of record. Of the top 20 most geomorphically active reaches surveyed in the County, 12 are in the Anacostia River basin, with the other scattered among the Patuxent River and Potomac River basins.

Estimation of water inflows to reservoirs of irrigation dams in the Guinea Savannah ecological zone of Ghana

ABSTRACT The study was carried out in the northern Ghana to estimate water inflows to nine reservoirs of irrigation dams for a period of 20 years (1999–2018) using the USDA Natural Resources Conservation Service Curve Number model. The key input parameters of the model were hydrologic soil group, rainfall amount, landuse/landcover, weighted curve number, antecedent moisture condition, and potential maximum soil moisture retention. The annual rainfall within the reservoir catchments was found to vary between 617.20 and 1,382.30 mm. The estimated annual runoff depths ranged from 54.10 to 125.55 mm. A high degree of positive correlation was found between rainfall and runoff depths with a coefficient of determination (R2) ranging from 79.80 to 90.70%. Hydrologic soil groups accounted for about 67.2 and 62.5% of the variation in runoff depth and percentage runoff, respectively. The estimated annual water inflows to the reservoirs ranged from 145,206 ± 125,814 m3/y at Gambibgo to 47,074,634 ± 4,395,860 m3/y at Tono. The variation in the annual water inflows and annual storage capacity recharge among the various reservoirs was noted to be influenced by reservoir size, catchment size, rainfall, and soil characteristics in the reservoir catchments.

Choosing the Right Tool: A Comparative Study of Wetland Assessment Approaches

There are over 700 aquatic ecological assessment approaches across the globe that meet specific institutional goals. However, in many cases, multiple assessment tools are designed to meet the same management need, resulting in a confusing array of overlapping options. Here, we look at six riverine wetland assessments currently in use in Montana, USA, and ask which tool (1) best captures the condition across a disturbance gradient and (2) has the most utility to meet the regulatory or management needs. We used descriptive statistics to compare wetland assessments (n = 18) across a disturbance gradient determined by a landscape development intensity. Factor analysis showed that many of the tools had internal metrics that did not correspond well with overall results, hindering the tool’s ability to act as designed. We surveyed regional wetland managers (n = 56) to determine the extent of their use of each of the six tools and how well they trusted the information the assessment tool provided. We found that the Montana Wetland Assessment Methodology best measured the range of disturbance and had the highest utility to meet Clean Water Act (CWA§ 404) needs. Montana Department of Environmental Quality was best for the CWA§ 303(d) & 305(b) needs. The US Natural Resources Conservation Service’s Riparian Assessment Tool was the third most used by managers but was the tool that had the least ability to distinguish across a disturbance, followed by the US Bureau of Land Management’s Proper Functioning Condition.

Are crop insurance discount programs for cover crops effective? Evidence from Iowa

AbstractCover crops are promoted by agronomists and governments due to their on‐farm and off‐farm benefits. Incentive programs were created because high planting costs have hindered cover crop adoption in the United States. Crop insurance discount programs are novel incentives that subsidize farmers’ crop insurance premiums by $5 per acre ($12.36 ha−1) on cover cropped land. While this payment is smaller than those typically offered through the Natural Resources Conservation Service and state‐level cost‐share programs, crop insurance discount programs have the potential to reach a significant proportion of farmers who purchase crop insurance. This paper uses data from a survey of Iowa farmers to quantify whether participation in the Iowa Crop Insurance Discount Program (ICIDP) affects the area planted to cover crops. I find that 11% of the ICIDP area would not have been planted to cover crops in the absence of the program, which is similar to other programs after considering the lower payment rate.

Leveraging Next‐Generation Satellite Remote Sensing‐Based Snow Data to Improve Seasonal Water Supply Predictions in a Practical Machine Learning‐Driven River Forecast System

AbstractSeasonal predictions of spring‐summer river flow volume (water supply forecasts, WSFs) are foundational to western US water management. We test a new space‐based remote sensing product, spatially and temporally complete (STC) MODSCAG fractional snow‐covered area (fSCA), as input for the Natural Resources Conservation Service (NRCS) operational US West‐wide WSF system. fSCA data were considered alongside traditional SNOTEL predictors, in both statistical and AI‐based NRCS operational hydrologic models, throughout the forecast season, in four test watersheds (Walker, Wind, Piedra, and Gila Rivers in California, Wyoming, Colorado, and New Mexico). Outcomes from over 200 WSF models suggest fSCA‐enabled accuracy gains are most consistent and explainable for short‐lead, late‐season forecasts (roughly 10%–25% improvements, typically), which in operational practice can be challenging as snowlines rise above in situ measurement sites. Gains are roughly proportional to how thoroughly spring‐summer runoff is dominated by snowmelt, and how poorly in situ networks monitor late‐season snowpack. fSCA also improved accuracy for long‐lead, early‐season forecasts, which are similarly problematic in WSF practice, but not for WSFs issued around the time of peak snow accumulation, when in situ measurements reasonably characterize mountain snowpack available for upcoming spring‐summer snowmelt. The AI‐based hydrologic model generally outperformed the statistical model and, in some cases, better‐capitalized on satellite remote sensing. Additionally, preliminary analyses suggest reasonable WSF skill in many cases using fSCA as the sole predictor, potentially useful in sparsely monitored regions; and that combining satellite and in situ products in data‐driven hydrologic models using genetic algorithm‐based predictor selection could help guide new SNOTEL site selection.

Soils information for urban customers: A perspective

AbstractDue to its benefits, including but not limited to increased access to affordable healthy food, bringing communities together for a common goal, and improving food security, urban agriculture is gaining popularity across the United States. Although soil‐based information is available at the national level, people in urban environments may have limited details about the soils in their communities. To bridge the gap between rural and urban agriculture, city, state, and federal agencies such as the Natural Resources Conservation Service could expand upon the soil survey programs that currently exist and are available within the WebSoilSurvey. Additionally, trace element testing and interpretation would allow for improved knowledge about the risks that urban soils may have on food quality for those interested in urban agriculture.Core Ideas Detailed soil science information for urban agriculture may be lacking on a fine scale. Opportunities exist to support the soil science needs of urban growers via local, state, and federal entities. Information on urban soils can help provide healthy and sustainable foodstuffs.

Simulation of Long-Term Water Erosion in Rainfed Croplands of Eastern Washington

Highlights Water erosion in the inland Pacific Northwest was modeled with WEPP for the past (1940–1982) and present (1983–2020). Water erosion decreased from past to present in the study watersheds. Major factors are increased adoption of conservation practices and decrease in large precipitation events. Abstract. Water erosion is an ongoing problem in eastern Washington due to its hilly terrain, highly erodible silt loam soils, rain on thawing soil, and the prevalence of conventional tillage. The region is characterized by a Mediterranean-type climate with warm, dry summers and cool, wet winters. Three distinct precipitation zones, with annual totals low (<380 mm), intermediate (380–460 mm), and high (>460 mm), dictate the area’s crop rotations. A unique 43-year (1940–1982) dataset of winter erosion measured on multiple agricultural fields in Whitman County, eastern Washington, by Verle Kaiser, a USDA Soil Conservation Service agronomist, showed annual erosion rates averaging 53.8 Mg ha-1, far exceeding the current Natural Resources Conservation Service tolerable limit of 11 Mg ha-1 yr–1 for the soils in the area. Kaiser’s field data allowed us to compare the historical field-measured erosion rates with those simulated by the WEPP (Water Erosion Prediction Project) model. Anthropogenic factors, such as tillage and crop rotation, change with time. Conservation tillage, including reduced- and no-till, has been increasingly adopted in eastern Washington since the mid-1980s. The specific objectives of this study were to (1) apply the WEPP model to simulate soil erosion in eastern Washington and evaluate the interactive effects of climate and management, in addition to topography and soil, on water erosion in the study area, and (2) compare the simulation results with Kaiser’s historical field dataset and elucidate the long-term soil erosion trend. The WEPPcloud interface was used to delineate a watershed within each precipitation zone of the study area. Climate inputs were divided into two periods: the past (1939–1982) and the present (1983–2020). Erosion has noticeably decreased from the past to the present, with WEPP simulated annual erosion averaging 13.5, 34.5, and 52.6 Mg ha-1 for the past, and 9.5, 14.1, and 15.5 Mg ha-1 for the present, in the selected watersheds in the low-, intermediate-, and high-precipitation zones, respectively. The decreasing trend was primarily due to the increased adoption of conservation tillage and crop rotation, as well as a decrease in the number of high-intensity precipitation events in the present climate. Keywords: Inland Pacific Northwest, Soil erosion by water, Temporal trend, WEPP.

Land reclamation and soil health in mining area

Soil is the foundation of food security, but also the cornerstone of biological health on Earth, healthy soil is a prerequisite for healthy living. The U.S. Department of Agriculture's Natural Resources Conservation Service defines soil health as the continued ability of soil to serve as an important biological ecosystem for the sustenance of plants, animals, and humans.

Winter-time cover crop identification: A remote sensing-based methodological framework for new and rapid data generation

Accurately identifying and systematically mapping winter-time cover crops and their phenological characteristics offer significant benefits to agricultural producers and policymakers, as cover crops are one of several potential solutions to climate change mitigation. We present a methodological framework for identifying and mapping the presence of winter-time cover crops at the field level and aggregated to county scales from 2013 to 2019 by using the Google Earth Engine (GEE), a random forest classifier with time series data from Landsat 8, and yearly cover crop training data from the United States Department of Agriculture (USDA)-Natural Resources Conservation Service (NRCS). The methodology was tested with data from the Mississippi Alluvial Plain (MAP) region. Despite the inter-annual agronomic and climatic variations across space, results demonstrated an overall mean classification accuracy of 97.7%, with a kappa coefficient of 0.94. Results also revealed a 34% increase in model-predicted cover crop adoption in the study region from 2013 to 2019. Based on GEE, this study created, for the first time, a 30-m spatial and temporal resolution binary annual datasets and then aggregated them at the county level within the MAP study region. This multi-year novel dataset may improve our ability to anticipate and quantify the impact of summer crop production gains owing to cover crop adoption for extended periods and evaluate the adoption of cover crops on local soil ecosystems, biogeochemical cycles, and services. The methodology developed and tested broadly applies to other regions where cover crops have been promoted for climate-change mitigation and improving soil health for long-term sustainability. Agricultural producers, policymakers, and cost-share providers may use this information to develop agricultural conservation methods and land-use policies that minimize soil erosion and help mitigate climate change effects in the long run.

Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model

Abstract. Convection-permitting regional climate models (RCMs) have recently become tractable for applications at multi-decadal timescales. These types of models have tremendous utility for water resource studies, but better characterization of precipitation biases is needed, particularly for water-resource-critical mountain regions, where precipitation is highly variable in space, observations are sparse, and the societal water need is great. This study examines 34 years (1987–2020) of RCM precipitation from the Weather Research and Forecasting model (WRF; v3.8.1), using the Climate Forecast System Reanalysis (CFS; CFSv2) initial and lateral boundary conditions and a 1 km × 1 km innermost grid spacing. The RCM is centered over the Upper Colorado River basin, with a focus on the high-elevation, 750 km2 East River watershed (ERW), where a variety of high-impact scientific activities are currently ongoing. Precipitation is compared against point observations (Natural Resources Conservation Service Snow Telemetry or SNOTEL), gridded climate datasets (Newman, Livneh, and PRISM), and Bayesian reconstructions of watershed mean precipitation conditioned on streamflow and high-resolution snow remote-sensing products. We find that the cool-season precipitation percent error between WRF and 23 SNOTEL gauges has a low overall bias (x^ = 0.25 %, s = 13.63 %) and that WRF has a higher percent error during the warm season (x^ = 10.37 %, s = 12.79 %). Warm-season bias manifests as a high number of low-precipitation days, though the low-resolution or SNOTEL gauges limit some of the conclusions that can be drawn. Regional comparisons between WRF precipitation accumulation and three different gridded datasets show differences on the order of ± 20 %, particularly at the highest elevations and in keeping with findings from other studies. We find that WRF agrees slightly better with the Bayesian reconstruction of precipitation in the ERW compared to the gridded precipitation datasets, particularly when changing SNOTEL densities are taken into account. The conclusions are that the RCM reasonably captures orographic precipitation in this region and demonstrates that leveraging additional hydrologic information (streamflow and snow remote-sensing data) improves the ability to characterize biases in RCM precipitation fields. Error characteristics reported in this study are essential for leveraging the RCM model outputs for studies of past and future climates and water resource applications. The methods developed in this study can be applied to other watersheds and model configurations. Hourly 1 km × 1 km precipitation and other meteorological outputs from this dataset are publicly available and suitable for a wide variety of applications.

Effects of forest management on private lands in West Virginia on Cerulean Warblers (Setophaga cerulea) and the avian community

The USDA Natural Resources Conservation Service (NRCS) supports private lands conservation projects across the United States to benefit imperiled focal wildlife species using conservation practices to restore habitat. The Cerulean Warbler Appalachian Forestland Enhancement Project (CWAFEP) was initiated in 2015 to help stabilize or reverse Cerulean Warbler population declines by using forest management to create or enhance breeding habitat on private lands in Appalachian focal areas. We evaluated Cerulean Warbler occupancy on CWAFEP sites treated using NRCS conservation practices to inform adaptive management strategies. We also assessed associated forest focal species’ occupancy and species richness of avian guilds to evaluate the effects of conservation practice implementation on the avian community. We conducted point count surveys at 194 locations on 21 private properties enrolled in the CWAFEP in West Virginia during May – July 2019 and 2020. We compared occupancy among four treatments: reference, pre-treatment, 1-year post-treatment, and 2 – 4 years post-treatment sites. To examine how vegetation structure changes among treatments affected occupancy, we also collected and included vegetation variables. Cerulean Warbler occupancy estimates were not different among treatments, suggesting that post-treatment study sites surveyed did not achieve their goal of increasing Cerulean Warbler occupancy. Cerulean Warbler occupancy decreased by 91 % as elevation increased from 200 to 800 m and increased by 397 % as sapling cover increased from 0 to 100 %. Occupancy for three forest focal species (Blue-gray Gnatcatcher, Eastern Wood-pewee, and Scarlet Tanager) and species richness of four avian guilds also were not different among treatments. Thus, Cerulean Warbler occupancy and selected avian community demographics were not related to recent conservation practice implementation in the short-term (1 – 4 years post-treatment), but there are opportunities to improve NRCS conservation practice implementation for more effective Cerulean Warbler conservation. We suspect that the lack of differences in occupancy and species richness estimates was due to site selection related to ecoregion, small treatment areas, and challenges associated with private lands conservation efforts resulting in insufficient reduction in basal area. If NRCS conservation practices implemented through CWAFEP are going to help reverse Cerulean Warbler population declines, CWAFEP sites need to achieve the recommended basal area range of ∼ 9.2 – 20.7 m 2/ha (40 – 90 ft2/ac) during contract implementation. Our conclusions are critical to updating our knowledge for Cerulean Warbler best management practices and informing future regional conservation implementation.

435 Opportunities for Conservation Research Support, Feed Management Planning and Practice Cost Sharing

Abstract The U.S. Department of Agriculture’s Natural Resources Conservation Service (NRCS) uses science-based technology to provide conservation planning and assistance to landowners, operators, producers, and others to benefit the soil, water, air, plants, animals, and energy for productive lands and healthy ecosystems. Learn about opportunities for financial and technical assistance for livestock production and conservation as well as grant programs for innovative conservation research and on-farm trials.

Farmer typologies integrating latent and observed characteristics: Insights for soil and water conservation outreach

One of the fundamental rules of effective communication is to “know your audience.” When engaging farmers in conservation in the U.S. and elsewhere where their participation is voluntary, communication should start with the fundamental recognition that farmers are heterogeneous in many ways; their attitudes, values, and motivations, as well as their farms’ biophysical and economic characteristics, can influence their behaviors. Previous typology research in Iowa, USA using data from a panel survey of farmers, revealed heterogeneity by identifying four types of farmers—Conservationists, Deliberative, Productivists, and Traditionalists—based on latent class analysis of variables measuring varied dimensions of awareness, attitudes, beliefs, perceived motivations, and barriers to practice adoption. The study presented in this article advances the typology by associating observable variables from the same survey (e.g., farmer demographics, farm enterprises, participation in conservation programs, adoption of conservation practices) with the four farmer types. The Conservationist type was the most educated and indicated a high intention of adopting cover crops. The Deliberative type tended not to have a conservation plan with the U.S. Department of Agriculture Natural Resources Conservation Service. The Productivist farmer farmed the most land, rented and owned, and had the highest no-till implementation in land size and percentage of the group. The Traditionalist type rented the least amount of land. We expect outreach professionals, watershed coordinators, and conservation practitioners can use observable characteristics to segment the farmer population and improve conservation messages by tailoring them to the specific farmer types, leading to a higher return on investment in terms of money, time, and goodwill.

Developing an Empirical Relations between Nash Model Parameters and Watersheds Topographical Characteristics for Predicting Direct Runoff Hydrograph

The limited availability of the recorded rainfall-runoff data for many watersheds restricts the development and management of different activities of water resources. To overcome this limitation, the Natural Resources Conservation Service (NRCS) for estimating storm excess rainfall and momentum and optimization methods were combined in a mathematical model to estimate the optimal parameters of Nash Instantaneous unit hydrograph (IUH) and resulting direct runoff hydrograph (DRH), using a developed computer program in MATLAB. The available recorded data of 14 storms (out of 18) of four watersheds in northern Iraq have been applied in the calibration stage. An empirical relationship was developed between the average of each IUH optimal parameter (obtained by optimization as an optimal method according to the applied tests) and the effective watershed topographical characteristics. The developed empirical relations were used in the verification stage to estimate the IUH parameters and DRH for the verification storms and compare with that resulted from Haan’s empirical relations and optimization method. The statistical tests showed that the developed empirical relations efficiency was better than that of Haan’s method and close to that of the recorded storm by optimization method, where the average value of the Nash-Sutcliffe Efficiency for the four watersheds resulted from applying the optimization method, Haan’s method and the developed empirical relations were 0.925, 0.587, 0.883 respectively. The results indicated the developed model’s ability to estimate the IUH and direct runoff hydrograph for ungauged watersheds in northern Iraq.

Root distributions, precipitation, and soil structure converge to govern soil organic carbon depth distributions

The depth distribution of soil organic carbon (SOC) is governed by the interaction of many ecosystem features, including differential C inputs in shallow and deep soils and the redistribution of C via water flow through the profile. In C-rich Mollisols in particular, we need to better understand the degree to which the conversion of native prairie to cultivated lands is changing C loss and retention. We probed multiple mechanisms driving these processes using two approaches: one leverages a regional-scale dataset derived from the Natural Resources Conservation Service (USDA-NRCS) National Cooperative Soil Survey (NCSS) Characterization Database; and a second focusses on a local-scale, more detailed dataset representative of the climatic and land-use gradients invoked in the larger database. The first approach focused on parameterizing SOC depth distributions of Mollisols across a climatic gradient in the US Midwest to investigate how land use and effective precipitation affects vertical gradients of SOC. The second approach furthered the investigation of SOC depth distribution drivers by quantifying biological, physical, and chemical properties of multiple soil profiles across Kansas, US. SOC declined more gradually with depth as water availability increased in native prairie soils, prompting the hypothesis that increased water flow through the profile carries C to deep layers, particularly where high root abundances promote soil porosity. Analyses of multiple soil profiles indicate that surficial changes driven by land conversion propagate their influence to deep soil horizons in ways significant for the coupling of C cycling across depths. Our findings support the hypothesis, and specifically suggest linkages between decreased root abundances and increased flows of soluble C downward under agriculture, and associated changes in soil structure that affect the propensity of SOC to form aggregates. The interplay between rooting depth abundances and water availability in different land uses thus appears to influence the arrangement of soils particles and voids in ways important for vertical water flow and C transport. Our work illuminates the convergence of multiple important mechanisms driving changes in the shape of SOC depth distributions across timescales shorter than typically assumed, with consequences for projecting soil C cycling and storage in the Anthropocene.

Diffuse pollutant load predictions in areas that implement the total maximum daily load due to climate change

Total maximum daily load (TMDL), which is implemented for water quality management in a watershed, necessitates the use of a watershed model to predict the load. However, such a model consumes a lot of time and effort until the results are simulated. Therefore, the present study aimed to compare and evaluate load changes following the revision of the land-based diffuse pollutant unit load values, which are used to calculate the diffuse pollutant discharge loads in the total maximum daily load (TMDL) guidelines established for TMDL control by watersheds in South Korea, using the Natural Resources Conservation Service (NRCS) method. When the revised unit load was used, the loads were reduced by an average of 56.8% compared with the prior unit load. The descending order of load change rate was biochemical oxygen demand (BOD) > total phosphorus (TP) > total nitrogen (TN). Although the difference in load discharge trends between the Representative Concentration Pathway (RCP) 2.6 and RCP8.5 scenarios was insignificant, the load discharge under the worst scenario (RCP8.5) may increase. When the future period was split into 30-year increments, the load of precipitation and diffuse pollutants increased in the intermediate future (2041–2070). This study examined how the management ratio of diffuse pollutants in a watershed changes when the legal standard value of institutionally managed diffuse pollutants changes. The findings of this study provide useful information for the efficient management of present and future diffuse pollutants.

Evaluation of the Storms Direct Runoff Prediction Methods used for Goizha-Dabashan Watershed

The Momentum and Aron & White evaluating methods have been adopted to estimate the Nash Instantaneous Hydrograph parameters (IUH), while the two methods of excess rainfall (Ф-index and Natural Resources Conservation Service (NRCS) were applied in a model using a developed computer program in MATLAB to predict the direct runoff hydrograph for Goizha-Dabashan watershed located in the northeast of Iraq. In the verification stage, both Nash IUH optimal parameters of the storms and the average optimal values of the same parameters estimated in the calibration stage were applied and compared. The statistical tests showed a preference for the NRCS method with the momentum method in estimating direct runoff hydrograph (the average Nash-Sutcliffe Efficiency (NSE) was equal to 0.815 and 0.77 using optimal parameters verification storms and the average calibrated IUH parameters values, respectively). Also, satisfactory results (NSE was equal to 0.77 and 0.76 using storm parameters and the average calibrated IUH parameters values, respectively) were obtained by applying Aron & White with the NRCS methods, which indicated the ability of both methods for estimating direct runoff hydrograph.

Estimated reduction of nitrogen in streams of the Chesapeake Bay in areas with agricultural conservation practices

Spatial data provided by the U.S. Department of Agriculture National Resource Conservation Service representing implementation at the field-level for a selection of agricultural conservation practices were incorporated within a spatially referenced regression model to estimate their effects on nitrogen loads in streams in the Chesapeake Bay watershed. Conservation practices classified as “high-impact” were estimated to be effective (p = 0.017) at reducing contemporary nitrogen loads to streams of the Chesapeake Bay watershed in areas where groundwater ages are estimated to be less than 14-years old. Watershed-wide, high-impact practices were estimated to reduce nitrogen loads to streams by 1.45%, with up to 60% reductions in areas with shorter groundwater ages and larger amounts of implementation. Effects of “other-impact” practices and practices in areas with groundwater ages of 14 years or more showed less evidence of effectiveness. That the discernable impact of high-impact practices was limited to areas with a median groundwater age of less than 14 years does not imply that conservation practices are not effective in areas with older groundwater ages. A model recalibrated using high-impact agricultural conservation practice data summarized by county suggests effects may also be detectable using implementation data available at such coarser resolution. Despite increasing investment, effects of agricultural conservation practices on regional water quality remain difficult to quantify due to factors such as groundwater travel times, varying modes-of-action, and the general lack of high-quality spatial datasets representing practice implementation.