Creek Watershed Research Articles

Spatial Distribution of Chesapeake Bay Riparian Hemlock Forests Threatened by Hemlock Woolly Adelgid

Abstract Landscape-scale maps of tree species densities are important tools for managing ecosystems threatened by forest pests. Eastern hemlock dominates riparian forests throughout its range. As a conifer in a deciduous landscape, hemlock plays an ecohydrological role, especially when other species are dormant. The nonnative, hemlock woolly adelgid has caused widespread hemlock decline and mortality. We used two existing basal area raster layers first to identify Chesapeake Bay subwatersheds with ≥6 percent hemlock basal area and second to quantify hemlock basal area densities within fixed-width riparian buffers of 50 m, 100 m, 250 m, and 500 m. Hemlock densities were higher in riparian zones compared with entire subwatersheds. In five subwatersheds, 50 m and 100 m zones had higher percentages of pixels with ≥25 percent hemlock basal area. We produced maps identifying hemlock riparian densities in the Pine Creek Watershed, which managers can use to prioritize sites for supplemental conifer planting under anticipated hemlock decline.

Fully distributed versus semi-distributed process simulation of a highly managed watershed with mixed land use and irrigation return flow

Spatially distributed process models represent soil-water-plant-nutrient interactions within a watershed. We investigated spatial patterns of water balance components and nitrate transport simulated using the fully distributed AgES (Agricultural Ecosystems Services) and the semi-distributed SWAT (Soil and Water Assessment Tool, 2012) models in the Big Dry Creek Watershed, a mixed agricultural and suburban watershed in semi-arid Colorado, USA. We analyzed patterns of hydrological fluxes using daily model outputs for the period 2010–2018. The two models simulated drastically different spatial patterns. SWAT predicted extremely low interflow and routed excess irrigation water to surface runoff and groundwater discharge. AgES produced realistic estimation of streamflow, irrigation return flows, and nitrate; simulation of less surface runoff and greater interflow and baseflow contributed to improved simulation of nitrate transport in the interior watersheds. This study demonstrated the impacts of simulating spatially explicit hydrology that captures interactions among fields and other areas within a managed watershed.

Stream Health Estimation for the Plum Creek Watershed

Overall health of a stream is one of the powerful indicators for planning mitigation strategies. Currently, available methods to estimate stream health do not look at all the different components of stream health. Based on the statistical parameters obtained from daily streamflow data, water quality data, and index of biotic integrity (IBI), this study evaluated the impacts on all the elements of stream health, such as aquatic species, riparian vegetation, benthic macro-invertebrates, and channel degradation for the Plum Creek watershed in Texas, USA. The method involved the (1) collection of flow data at the watershed outlet; (2) identification of hydrologic change in the streamflow; (3) estimation of hydrologic indicators using NATional Hydrologic Assessment Tool (NATHAT) before alteration and after alteration periods; (4) identification of the most relevant indicators affecting stream health in the watershed based on stream type; (5) preliminary estimation of the existence of stream health using flow duration curves (FDCs); (6) the use of stream health-relevant hydrologic indices with the scoring system of the Dundee Hydrologic Regime Assessment Method (DHRAM). The FDCs plotted together for before and after the alteration periods indicated the likely presence of a stream health problem in the Plum Creek. The NATHAT–DHRAM method showed a likely moderate impact on the health of Plum Creek. The biological assessments carried out, the water quality data monitored, and the land cover during pre- and post-alteration periods documented in a publicly available federal document support the stream health results obtained from this study.

Integrating Daily CO2 Concentrations in SWAT-VSA to Examine Climate Change Impacts on Hydrology in a Karst Watershed

HighlightsWe used SWAT-VSA to assess the effects of climate change with rising CO2 on the water balance of a karst basin.For future climate, SWAT-VSA with rising CO2 yielded 7.1% less ET and 6.3% more runoff than standard SWAT-VSA.Rising CO2 also affected variable source areas, with greater ET declines and runoff increases in the wettest soils.Findings suggest CO2 effects on water balance should be included in future climate change studies with SWAT-VSA.Abstract. Characterizing the effects of climate change on hydrology is important to watershed management. In this study, we used SWAT-VSA to examine the effects of climate change and increasing atmospheric CO2 (CO2) on the water balance of Spring Creek watershed, a mixed land-use karst basin in the Upper Chesapeake Bay watershed. First, we modified the stomatal conductance and leaf area index (LAI) routines of SWAT-VSA’s Penman-Monteith evapotranspiration (ET) procedure and enabled the model to accept daily CO2 data. Using downscaled climate projections from nine global climate models (GCMs), we then compared water balance estimations from baseline SWAT-VSA against two modified versions of SWAT-VSA. One SWAT-VSA version integrated daily CO2 levels (SWAT-VSA_CO2), while another version added flexible stomatal conductance and LAI routines (SWAT-VSA_CO2+Plant) to the dynamic CO2 capacity. Under current climate (1985-2015), the three SWAT-VSA models produced generally similar water balance estimations, with 51% of precipitation lost to ET and the remainder converted to runoff (10%), lateral flow (9%), and percolate (30%). For future climate (2020-2065), water balance simulations diverged between baseline SWAT-VSA and the two modified SWAT-VSA models with CO2. Notably, variable stomatal conductance and LAI routines produced no detectable effects beyond that of CO2. For the 2020-2065 period, baseline SWAT-VSA projected ET increases of 0.7 mm year-1, while SWAT-VSA models with CO2 suggested that annual ET could decline by approximately -0.4 mm year-1 over the same period. As a result, the two CO2-based SWAT-VSA models predicted streamflow increases of almost 1.6 mm year-1 over the 2020-2065 period, which were roughly double the streamflow increases projected by baseline SWAT-VSA. In general, SWAT-VSA models with CO2 effects produced 22.4% more streamflow in 2045-2065 than the SWAT-VSA model without CO2. Results also showed that adding daily CO2 to SWAT-VSA reduced ET in wetter parts of Spring Creek watershed, leading to greater runoff losses from variable source areas compared to baseline SWAT-VSA. Findings from the study highlight the importance of considering increasing atmospheric CO2 concentrations in water balance simulations with SWAT-VSA in order to gain a fuller appreciation of the hydrologic uncertainties with climate change. Keywords: Carbon dioxide, Climate change, Hydrologic model, Water balance, Watershed.

Microbial Source Tracking in the Love Creek Watershed, Delaware (USA).

Fecal contamination of waterways in Delaware pose an ongoing problem for environmental and public health. For monitoring efforts, Enterococcus has been widely adopted by the state to indicate the presence of fecal matter from warm-blooded animals and to establish Primary and Secondary Contact Recreation criteria. In this study, we examined sites within the Love Creek watershed, a tributary of the Rehoboth bay, using next-generation sequencing and SourceTracker to determine sources of potential fecal contamination and compared to bacterial communities to chemical and nutrient concentrations. Microbial community from fecal samples of ten different types of animals and one human sample were used to generate a fecal library for community-based microbial source tracking. Orthophosphate and total dissolved solids were among the major factors associated with community composition. SourceTracker analysis of the monthly samples from the Love Creek watershed indicated the majority of the microbial community were attributed to “unknown” sources, i.e. wildlife. Those that attribute to known sources were primarily domestic animals, i.e. cat and dog. These results suggest that at the state level these methods are capable of giving the start for source tracking as a means to understanding bacterial contamination.

不同生态修复措施和环境因素对亚热带红壤区针叶纯林坡面水土保持功能的影响

使用"地理探测器（GeoDetector）"对亚热带红壤区水土流失影响因素的定量分析结果可为当地森林生态修复和侵蚀模型完善提供科学依据。基于福建省龙岩市新罗区龙门溪小流域森林调查数据和径流小区监测数据，利用地理探测器探测不同生态修复措施和环境因素对针叶纯林坡面水土保持功能的影响及交互作用，结果表明：（1）对比中幼龄针叶纯林，补植阔叶树使针阔混交比例为7 ： 2可减少46%的径流量和76%的泥沙量，生态修复效果较好。对重侵蚀区"老头树"少量施肥难以产生效果。（2）影响坡面径流的因素由强到弱依次是：降雨因子（0.53），土壤容重、林分密度、灌草层盖度、树高和针阔比（均在0.08左右）；影响泥沙流失的因素依次是：地表径流量（0.84），降雨因子（0.2），林分密度、土壤容重、灌草层盖度、土壤含水率、灌草层生物量（均在0.12左右）。（3）各影响因素交互后主要呈增强作用；林分密度、灌草层盖度和土壤容重还可与其他因子产生强烈非线性增强作用（交互后影响力>0.9），是在森林修复和模型参数优化时需重点关注的对象。;The quantification results of the GeoDetector for the impact factors of the soil and water loss in the subtropical red soil area provide the scientific base for the local forest ecological restoration and the improvement of erosion models. This study explored the direct and interactive influences of different ecological restoration measures and environmental factors on water and soil conservation of the slope in forest by introducing the GeoDetector and using the forest survey data and the observation data of the runoff plots in Longmen Creek Watershed, Xinluo District, Longyan City, Fujian Province. The results showed that:(1) to compared with the middle and young age pure coniferous forest, the mixed conifer-broadleaf forest with the mixed ratio 7:2 could cut down the runoff and sediment load by 46% and 76%, respectively which represented that the ecological restoration effect of this measure was excellent. The small amount of fertilization hardly worked on the old tree in the heavy erosion area. (2) The rank of the strong impact factors of the runoff of the slope was rainfall (q value was 0.5), soil bulk density, stand density, shrub coverage, tree height and forest mixed ratio (q values were around 0.08). The rank of the strong impact factors of the sediment loads was surface runoff (q value was 0.84), rainfall (q value was 0.2), stand density, soil bulk density, shrub coverage, soil moisture content, total biomass of shrub (q values were around 0.12). (3) There were complex interactions among the factors of soil and water conservation function. The enhance effect mode accounted for most of the total pairs of the interactions between two factors. The interaction between the weak factors (such as stand density, shrub coverage, and soil bulk density, etc.) and other factors could result in the nonlinear enhancement, and the influence was greater than 0.9. Therefore, they should be paid more attentions when we performed the forest restoration and model parameter optimization.

Hydrological Simulation of Silver Creek Watershed using Soil and Water Assessment Tool (SWAT)

Silver Creek Watershed has a basin of 1213.11 km2, located in Southern part of Illinois State (U.S.A), including highland silver lake and its east fork tributary. This research employs (Soil and Water Assessment Tool) to analyze the watershed as a function of land use parameters. Diff erent parameters have been considered in sensitivity analysis to determine the most sensitive parameters for fl ow rate calibration within diff erent hydrological response units (HRUs). Inputs parameters include precipitations and meteorological data such as solar radiation, wind speed and direction, temperature, and relative humidity. Model was calibrated with measured daily data for Troy gage station. The main objective was to simulate and calibrate the fl ow rate with SWAT model. Uncertainty analysis has been performed with SUFI-2 (Sequential Uncertainty Fitting Version-2) which is interfaced with SWAT applying iSWAT (generic coupling format program). Correlation between several stations within the domain has been calculated which showed a good range of Correlation (R2) values which means the pattern of meteorological data was evenly distributed. Finally based on the root mean of squares error (RMSE), (R2), NSE, and P-BIAS values, the accuracy of the calibration has been determined

1420. A One Health Approach Examining the Potential Linkage between Agricultural Livestock and Human Antibiotic Resistance at the Watershed Level

BackgroundAntibiotic resistance is a significant public health threat and widespread use of antibiotics in agriculture is increasing the concern about agricultural contributions to the dissemination of antibiotic resistant bacteria. Of concern is the level of exposure to antibiotics and antibiotic-resistant bacteria in the watershed. Consequently, adopting a One Health approach to measure antibiotic levels and identify antibiotic resistance gene (ARG) transfer at the human, animal and environmental interfaces is essential to better understand how antibiotic resistance is spread.MethodsIn this project, antibiotic levels were measured using passive organic chemical integrative samplers (POCIS) for 30-day periods from August – November 2018 from Elkhorn River and Shell Creek watersheds in Nebraska (Figure 1). In addition, whole genome sequences of bacterial isolates cultured from the watersheds were assessed to identify ARGs present on mobile genetic elements (MGE) that had >95% similarity to mobile ARG present in isolates recorded in the NCBI GenBank database was identified using ResFinder.Figure 1. Sampling locations within the two watersheds.ResultsThe study demonstrated significant antibiotic levels present throughout the watershed, with five of them associated with human usage (Table 1). In addition, seasonally based drug-resistant bacterial species was associated with specific antibiotic levels in the watershed (Figure 2). Mobile ARGs were detected in 87.5% of isolates collected from the Elkhorn River and 80.0% within Shell Creek (Figure 3). Table 1. Pharmaceutical levels in the watershed Figure 2. Antibiotic levels and drug-resistant bacteria in the watershed Figure 3. Antibiotic resistance observed from each isolate at every sampling date and site. A colored bar denotes that resistance to that antibiotic was observed. ConclusionThese results present evidence of transfer of highly mobile ARGs between environment, clinical, and animal-associated bacteria and highlight the need for a One Health perspective in assessing the spread of antibiotic resistance. The presence of significant levels of antibiotics persisting in this agricultural watershed points out the need for ongoing monitoring of compliance with the Food and Drug Administration (FDA) recommendation of veterinarian oversight of the use of antibiotics in the use of veterinary feed directive applications.Disclosures All Authors: No reported disclosures

Modeling and Prioritizing Interventions Using Pollution Hotspots for Reducing Nutrients, Atrazine and E. coli Concentrations in a Watershed

Excess nutrients and herbicides remain two major causes of waterbody impairment globally. In an attempt to better understand pollutant sources in the Big Sandy Creek Watershed (BSCW) and the prospects for successful remediation, a program was initiated to assist agricultural producers with the implementation of best management practices (BMPs). The objectives were to (1) simulate BMPs within hotspots to determine reductions in pollutant loads and (2) to determine if water-quality standards are met at the watershed outlet. Regression-based load estimator (LOADEST) was used for determining sediment, nutrient and atrazine loads, while artificial neural networks (ANN) were used for determining E. coli concentrations. With respect to reducing sediment, total nitrogen and total phosphorus loads at hotspots with individual BMPs, implementing grassed waterways resulted in average reductions of 97%, 53% and 65% respectively if implemented all over the hotspots. Although reducing atrazine application rate by 50% in all hotspots was the most effective BMP for reducing atrazine concentrations (21%) at the gauging station 06883940, this reduction was still six times higher than the target concentration. Similarly, with grassed waterways established in all hotspots, the 64% reduction in E. coli concentration was not enough to meet the target at the gauging station. With scaled-down acreage based on the proposed implementation plan, filter strip led to more pollutant reductions at the targeted hotspots. Overall, a combination of filter strip, grassed waterway and atrazine rate reduction will most likely yield measureable improvement both in the hotspots (>20% reduction in sediment, total nitrogen and total phosphorus pollution) and at the gauging station. Despite the model’s uncertainties, the results showed a possibility of using Soil and Water Assessment Tool (SWAT) to assess the effectiveness of various BMPs in agricultural watersheds.

Evaluation of AnnAGNPS Model for Runoff Simulation on Watersheds from Glaciated Landscape of USA Midwest and Northeast

Runoff modeling of glaciated watersheds is required to predict runoff for water supply, aquatic ecosystem management and flood prediction, and to deal with questions concerning the impact of climate and land use change on the hydrological system and watershed export of contaminants of glaciated watersheds. A widely used pollutant loading model, Annualized Agricultural Non-Point Source Pollution (AnnAGNPS) was applied to simulate runoff from three watersheds in glaciated geomorphic settings. The objective of this study was to evaluate the suitability of the AnnAGNPS model in glaciated landscapes for the prediction of runoff volume. The study area included Sugar Creek watershed, Indiana; Fall Creek watershed, New York; and Pawcatuck River watershed, Rhode Island, USA. The AnnAGNPS model was developed, calibrated and validated for runoff estimation for these watersheds. The daily and monthly calibration and validation statistics (NSE > 0.50 and RSR < 0.70, and PBIAS ± 25%) of the developed model were satisfactory for runoff simulation for all the studied watersheds. Once AnnAGNPS successfully simulated runoff, a parameter sensitivity analysis was carried out for runoff simulation in all three watersheds. The output from our hydrological models applied to glaciated areas will provide the capacity to couple edge-of-field hydrologic modeling with the examination of riparian or riverine functions and behaviors.

Estiagens, secas e os processos de arenização na Bacia Hidrográfica do Arroio Miracatu, sudoeste do estado do Rio Grande do Sul

<p>Os processos de arenização no sudoeste do Rio Grande do Sul são altamente dinâmicos, ora por meio da água, ora por ação dos ventos que remobilizam as exposições arenosas nos períodos com ausência de chuva. Assim, tanto o excesso como a escassez pluviométrica são fundamentais para a compreensão desses processos. Partindo desse pressuposto, o presente trabalho visa a analisar a ocorrência de estiagens e secas considerando uma série de dados pluviométricos (1970-2015) coletados na Bacia Hidrográfica do Arroio Miracatu, local este onde se encontra a maior extensão de áreas em processo de arenização. Considerando a metodologia empregada para a determinação de episódios de estiagem (períodos com mais de 15 dias sem chuva), constatou-se que houve registros em praticamente todos os anos estudados (exceto um). Mensalmente, a distribuição piramidal dos episódios coloca o trimestre maio-julho como o mais propício, embora possam ocorrer em qualquer época do ano. Contudo, a maior frequência de estiagens na década de 1970 é reflexo de um grande período seco, cuja determinação foi possível a partir do Índice Padronizado de Seca Pluviométrica.</p><p>Abstract</p><p>DRY PERIODS, DROUGHTS AND THE SANDIZATION PROCESSES IN MIRACATU CREEK WATERSHED, SOUTHWEST OF RIO GRANDE DO SUL STATE, BRAZIL</p><p>The sandization processes in the southwest of Rio Grande do Sul State are highly dynamic, sometimes through water action, sometimes due to winds action that remobilize sandy deposits in dry periods with no rain. Thus, both the excess and the absence of rain are fundamental for understanding this process. Based on this assumption, the present work aims to analyze the occurrence of droughts and dry periods considering a rainfall data series (1970-2015) collected in the Miracatu Creek Watershed, site where there is the largest extension of areas in the sandization process. Considering the methodology used to determine drought episodes (periods with more than 15 consecutives dry days), it was found that there were records in practically every year studied (except one). Monthly, the pyramidal distribution of episodes puts the May July quarter as the most favorable, although they can occur at any time of the year. However, the greater frequency of droughts in the 1970s reflects a long dry period, whose determination was possible based on the Standardized Precipitation Index.</p>

An empirical modeling approach to predicting pollutant loads and developing cost-effective stormwater treatment strategies for a large urban watershed

Stormwater treatment strategies were evaluated for the upper Ballona Creek Watershed in Los Angeles, CA using an empirical model of stormwater runoff quantity and quality with zeroth-order regularization and a limited memory Broyden-Fletcher-Goldfarb-Shanno Bound constrained optimization routine. The model used landuse based estimation on the runoff volume, event mean concentration (EMC) and pollutant load employing ten different landuses, including highways and local roads. The model was validated by showing that its predictions were in reasonable agreement (r2 ~0.6 to 0.8) with total zinc (Zn), Total Kjeldahl Nitrogen (TKN), and Total Suspended Solids (TSS) loadings measured at the monitoring site at the bottom of the watershed. The developed model was used to demonstrate and quantify the benefits of the stormwater treatment practices (STPs) prioritized at specific landuses with high pollutant mass emission rates. For this demonstration, total Zn was selected as it is one of the most concerning pollutants in an extremely urbanized area such as the Ballona Creek Watershed. Transportation landuse including local roads and highways was found to be the best candidate for the STP applications due to their high percent load contribution per percent area. By focusing STPs for transportation landuse, the water quality goal of total Zn in the study watershed was expected be achieved at approximately 75% less cost.

Groundwater from perennial springs provide refuge from wildfire impacts in mountainous semiarid watershed

Warming temperatures, earlier snowmelt, and the elongation of dry seasons are contributing to the propensity for more frequent and severe wildfires in semiarid, mountainous watersheds, which act as source watersheds for communities, especially in the southwestern United States. Research on how vegetation and water sources will respond following wildfires in these watersheds is critical for water resource, land, and forest managers. Little research has been completed on the effect of groundwater discharged from springs on revegetation of burned forests. We test whether springs, as perennial sources of water in semiarid watersheds, have the potential to protect roots and seeds from being damaged and facilitate the regrowth of native vegetation in areas affected by wildfires, thereby creating zones of fire refugia and mitigating the propensity for floods, erosion, and incursion of invasive species. The effect of springs on revegetation is studied in the Asaayi Creek Watershed located in the Chuska Mountains, NM/AZ, and in the Royal Gorge Park located near Cañon City, CO. In the Asaayi Creek watershed, remote sensing imagery and ground surveys show that springs facilitated revegetation following a June 2014 wildfire. Post-fire time lapse photography reveal more abundant vegetation around springs and more diverse vegetation in areas where there are multiple springs. Significantly higher Enhanced Vegetative Index (EVI) values are observed around perennial springs in the Asaayi Creek watershed and also around intermittent springs in the Royal Gorge area, one year after wildfires occurred in each study area. However, the revegetation around the perennial springs in the Asaayi Creek Watershed is widespread compared to Royal Gorge. There are multiple perennial springs that are clustered close together in Asaayi Creek Watershed, and only three intermittent flowing springs are located in the Royal Gorge burn area. Springs in the Asaayi Creek watershed provide a critical source of water that directly impacts soil moisture near the springs and in turn, protects roots and buds allowing native vegetation to regenerate.

Increasing plant water stress and decreasing summer streamflow in response to a warmer and wetter climate in seasonally snow‐covered forests

AbstractWarming temperatures and precipitation changes are expected to alter water availability and increase drought stress in western North America, yet uncertainties remain in how concurrent changes in the amount and seasonality of precipitation interact with warming to affect hydrologic partitioning. We combined over a century of streamflow (Q) and climate observations with two decades of tree growth data and remotely sensed vegetation activity to quantify how temperature and precipitation interact to control hydrologic partitioning in the Front Range of Colorado, Boulder Creek Watershed. Temperature and precipitation significantly increased over the last five decades, with precipitation increasing primarily in winter (11.2 mm decade−1) and temperature increasing primarily during the growing season (0.12°C decade−1). In response to wetter winters and warmer summers, streamflow decreased −9.8 mm decade−1, with largest declines occurring during summer and autumn baseflow (−8.4 mm decade−1). Spring warming was associated with increases in episodic, short spring melt events, earlier and slower snowmelt and an increase in fraction of precipitation available to plants (catchment wetting or W). Warming during the growing season resulted in an increase in the fraction of W lost as evapotranspiration (ET), earlier and lower peaks in remotely sensed normalized difference vegetation index (NDVI) and lower tree ring width index (RWI). These analyses highlight that vegetation is becoming increasingly water limited even as increases in precipitation and slower melt increase plant water availability. Further, catchment‐derived metrics like the Horton Index (ET/W) provide insight in to how simultaneous changes in temperature, precipitation and melt impact vegetation across complex watersheds.

Developing Sensor Proxies for “Chemical Cocktails” of Trace Metals in Urban Streams

Understanding transport mechanisms and temporal patterns in the context of metal concentrations in urban streams is important for developing best management practices and restoration strategies to improve water quality. In some cases, in-situ sensors can be used to estimate unknown concentrations of trace metals or to interpolate between sampling events. Continuous sensor data from the United States Geological Survey were analyzed to determine statistically significant relationships between lead, copper, zinc, cadmium, and mercury with turbidity, specific conductance, dissolved oxygen, and discharge for the Hickey Run, Watts Branch, and Rock Creek watersheds in the Washington, D.C. region. We observed a significant negative linear relationship between concentrations of Cu and dissolved oxygen at Rock Creek (p < 0.05). Sometimes, turbidity had significant positive linear relationships with Pb and Hg concentrations. There were negative or positive linear relationships between Pb, Cd, Zn, and Hg and specific conductance. There also appeared to be relationships between watershed areal fluxes of Pb, Cu, Zn, and Cd in streams with turbidity. Watershed monitoring approaches using continuous sensor data have the potential to characterize the frequency, magnitude, and composition of pulses in concentrations and loads of trace metals, which could improve the management and restoration of urban streams.

Water Soil Erosion Evaluation in a Small Alpine Catchment Located in Northern Italy: Potential Effects of Climate Change

Water erosion and evaluation of the average annual soil loss considering the potential effects of climate change are the focus of this study, based on the application of two empirical models, the RUSLE (Revised Universal Soil Loss Equation) and the EPM (Erosion Potential Method), to an Italian case study. A small mountain basin, the Guerna creek watershed, is located in the Central Southern Alps (Lombardy, Southern Alps, Bergamo), and it has been affected in the past by flooding and erosion events, which stressed the hydraulic weaknesses of the study area. Three different future climate scenarios were built for the middle of this century (from 2041 to 2060) on the basis of CORDEX data and Representative Concentration Pathways (RCP) set by the IPCC (Intergovernmental Panel on Climate Change) future scenarios: RCP 2.6, RCP 4.5, and RCP 8.5. As concerns climate, precipitation and air temperature are the variables used in the empirical models. On the other hand, potential effects on land use were also considered. Computed soil loss of 87 t/ha/year and 29.3 t/ha/year was achieved using the RUSLE equation and EPM method respectively, without considering the potential effects of climate change. The results achieved showed that climate change impacts on water erosion may not be negligible even by the middle of the current century (the annual average soil loss could change by 6–10% on a basin scale), and a major role is being played by seasonality in rainfall peak intensity.

Integration of Adaptive Emulators and Sensitivity Analysis for Enhancement of Complex Hydrological Models

A hydrological system involves a significant number of parameters to describe the real-world phenomena which ultimately reflects into the computational burden during model fitting and simulation. In this study, the proposed Adaptive Emulator Modelling based Optimization (AEMO) framework is presented which minimizes the complexity and computational burden, and enhances the overall efficiency of the representation of a physical watershed model. Here, AEMO consists of machine learning, sensitivity analysis, adaptive modelling, and sampling. The efficacy of the proposed AEMO framework is carried out through the Soil and Water Assessment Tool (SWAT) hydrological model for Peachtree Creek Watershed, Atlanta, USA. This watershed is subjected to flash floods in case of heavy rains due to a number of narrow streams situated in urban areas, and the water levels can rise quickly within a few hours or minutes of a rainfall event. Hence, this type of watershed is more complicated during the simulation and it is necessary to analyze the sensitivity during calibration of each iteration to provide information for the next iteration. The results concluded that the AEMO achieved exceptional results in both performance and computational burden when compared to the existing method. The NSE performance metric for the default SWAT model and hybrid model (SWAT + AEMO) showed the values 0.49 and 0.81, respectively. Hence, it displayed that AEMO enhanced the SWAT conceptual model prediction. The proposed framework incorporating future climate data can provide accurate information on water and disaster management.

Application of soft-computing techniques in forecasting sediment load and concentration

ABSTRACT This paper investigates conventional and soft-computing methods for the estimation of suspended sediment concentration (SSC) and load (SSL) in rivers. Frequently used methods of sediment rate curve (SRC) and multi-nonlinear regression, and soft-computing methods of multi-layer perceptron, multi-linear regression and adaptive neuro-fuzzy inference system are implemented using various hydrological and hydraulic parameters for the Little Kickapoo Creek Watershed, Illinois, USA. All methods performed equally well in the estimation of SSL, without any noticeable outperformance from any from the methods. However, the application of soft-computing methods decreased SSC estimation errors considerably as compared to the results of SRC. The results are significant in the way they reconcile traditionally used hydrological parameters into the soft-computing methods. Overall, soft-computing methods are recommended for the estimation of SSC in rivers because of their reasonably better performance and ease of implementation.

Sensitivity of Streamflow Metrics to Infiltration‐Based Stormwater Management Networks

AbstractAs stormwater control measures (SCMs) capture surface runoff from impervious areas, a shift in the water balance and flow regime components may emerge in urban watersheds, but the amount of SCM treatment needed to detectably shift these components may vary. We used the Soil and Water Assessment Tool (SWAT) hydrologic model to assess the sensitivity of 16 hydrologic metrics as an increasingly dense rain garden SCM network was applied across the West Creek watershed, near Cleveland, Ohio (USA). As the area treated by SCMs increased, annual baseflow increases matched decreases in surface runoff, while water yield and evapotranspiration changes remained small. The stream's peak response to rainfall decreased with SCM implementation across storm sizes, ranging from the threshold rainfall depth (4.8 mm) to values higher than the design storm of a single rain garden (19 mm). SCM networks draining >20% of directly connected impervious area (DCIA) significantly decreased the magnitude of discharges with a return period of less than 1 year, the percentage of time above mean flow, and flashiness. Recession slopes and annual 1‐ and 7‐day low flows exhibited a slight response that fell within uncertainty limits of the model. Water balance and rainfall response metrics exhibited the greatest sensitivity to different intensities of stormwater management, while infrequent high and low flows were resistant to detectable change even at high levels of SCM treatment when model uncertainty was included.

Drivers of excess phosphorus and stream sediments in a nested agricultural catchment during base and stormflow conditions.

A variety of landscape and hydrological characteristics influence nutrient concentrations and suspended sediments in freshwater systems, yet the combined influence of these characteristics within nested agricultural catchments is still poorly understood, particularly across varying flow states. To tease apart potential drivers at within-catchment scales, it is necessary to sample at a spatiotemporal resolution that captures how landscape drivers change with time. The overall objective of this study was to evaluate the relative influence of landscape and hydrological characteristics at sub-catchment scales in relation to total P (TP), soluble reactive P (SRP), the ratio of SRP and TP (SRP/TP), and total suspended solids (TSS) across varying flow conditions. Synoptic surveys were conducted at 13 longitudinal sampling sites under a variety of flow conditions (n=14) between 2016 and 2017 in the Innisfil Creek watershed, southern Ontario. The surveys were grouped into baseflow and stormflow conditions, and partial least squares regression (PLSR) was used to characterize the relationships between catchment characteristics, median concentrations of P, and TSS. Soil texture (i.e., clay dominated), winter wheat (Triticum aestivum L.), and constructed drain density had the largest influences on stormflow SRP and SRP/TP ratios, but measures of soil erosion, like the Bank Erosion Hazard Index and sinuosity, had the largest influence on stormflow TSS. During baseflow periods, these landscape characteristics were not informative, and they were difficult to tie to in-stream conditions. Overall, our PLSR models indicated that buried tile drainage was a major source of SRP in Innisfil Creek, whereas bank erosion was a dominant source of TSS.