Research Watershed Research Articles

Temperature and Flow Control Organic Carbon Metabolism in Boreal Headwater Streams

AbstractMetabolism in stream ecosystems alters the fate of organic carbon (OC) received from surrounding landscapes, but our understanding of in‐stream metabolic processes in boreal ecosystems remains limited. Determining the factors that regulate OC metabolism will help predict how the C balance of boreal streams may respond to future environmental change. In this study, we addressed the question: what controls OC metabolism in boreal headwater streams draining catchments with discontinuous permafrost? We hypothesized that metabolism is collectively regulated by OC reactivity, phosphorus availability, and temperature, with discharge modulating each of these conditions. We tested these hypotheses using a combination of laboratory experiments and whole‐stream ecosystem metabolism measurements throughout the Caribou‐Poker Creeks Research Watershed (CPCRW) in Interior Alaska, USA. In the laboratory experiments, respiration and dissolved OC (DOC) removal were both co‐limited by the supply of reactive C and phosphorus, but temperature and residence time acted as stronger controls of DOC removal. Ecosystem respiration (ER) was largely predicted by discharge and site, with some variance explained by gross primary production (GPP) and temperature. Both ER and GPP varied inversely with watershed permafrost extent, with an inverse relationship between temperature and permafrost extent providing one plausible explanation. Our results provide some of the first evidence of a functional response to permafrost thaw in stream ecosystems and suggest the role of metabolism in landscape C cycling may increase as climate change progresses.

The LTAR Cropland Common Experiment at Upper Mississippi River Basin-Morris.

The Upper Mississippi River Basin (UMRB) Long-Term Agroecosystem Research (LTAR) watershed is hydrologically complex, with a notable temperature and precipitation gradient across four locations: Ames, IA; Platteville, WI; Morris, MN; and St. Paul, MN. Each location established LTAR Croplands Common Experiment (CCE) scenarios to fit local climatic and cultural practices. This paper describes the UMRB-Morris location, which was established in 2016 and is the most northern of the sites and contributes to the major watersheds of the UMRB and the Red River of the North. Both on-farm and plot-scale studies are included. The prevailing system is a corn (Zea mays L.)-soybean (Glycine max L.) rotation with annual deep ripping tillage. The signature alternative system is alternative 1, which is a shallow strip-till in a corn-soybean rotation. A second alternative system includes shallow tillage/rotational no-tillage in a corn-soybean-wheat (Triticum aestivum L.) with winter oilseed and cover crops, and it is considered a test ground for future alternative systems. On-farm fields are equipped with eddy covariance towers and include 16 geo-referenced soil core sampling sites for incremental samplings. Each field is sampled annually for crop yield and management data are recorded. Plot-scale versions of the treatments are managed at the Swan Lake Research Farm. On-farm and plot-scale fields are instrumented with Phenocams to capture continuous photographic records. The CCE at UMRB-Morris aims to integrate soil, crop, weather data, and image classification to assess benefits and challenges across different management strategies.

An automated machine learning approach for detecting anomalous peak patterns in time series data from a research watershed in the northeastern United States critical zone

This paper presents an automated machine learning framework designed to assist hydrologists in detecting anomalies in time series data generated by sensors in a research watershed in the northeastern United States critical zone. The framework specifically focuses on identifying peak-pattern anomalies, which may arise from sensor malfunctions or natural phenomena. However, the use of classification methods for anomaly detection poses challenges, such as the requirement for labeled data as ground truth and the selection of the most suitable deep learning model for the given task and dataset. To address these challenges, our framework generates labeled datasets by injecting synthetic peak patterns into synthetically generated time series data and incorporates an automated hyperparameter optimization mechanism. This mechanism generates an optimized model instance with the best architectural and training parameters from a pool of five selected models, namely Temporal Convolutional Network (TCN), InceptionTime, MiniRocket, Residual Networks (ResNet), and Long Short-Term Memory (LSTM). The selection is based on the user’s preferences regarding anomaly detection accuracy and computational cost. The framework employs Time-series Generative Adversarial Networks (TimeGAN) as the synthetic dataset generator. The generated model instances are evaluated using a combination of accuracy and computational cost metrics, including training time and memory, during the anomaly detection process. Performance evaluation of the framework was conducted using a dataset from a watershed, demonstrating consistent selection of the most fitting model instance that satisfies the user’s preferences.

Forest Restoration in an Abandoned Seasonally Dry Tropical Forest in the Mae Klong Watershed, Western Thailand

Deforestation for the development of agricultural land is a critical driver of biodiversity loss. We examined the relationships between tree species and environments after the abandonment of a plot of land at the Mae Klong Watershed Research Station, Western Thailand. Vegetation monitoring was conducted every two years on a 16-ha permanent plot established in 2011 until 2019. All trees with diameter at breast height (DBH)≤1 cm were measured. Canonical correspondence analysis (CCA) was performed to investigate the relationships between tree species and environments. We found a total of 199 tree species in the plot, which comprised both pioneer and climax species. The high tree density and low basal area were 1,280 stem/ha and 7.30 m2/ha, respectively. During 2011-2019, the species richness and total tree density were decreased by nine species (from 206 to 197 species) and 83 stem/ha (from 1,120 to 1,037 stem/ha). In contrast, the total basal area increased from 6.41 to 7.26 stem/ha. According to the measured environmental variables, mixed deciduous species such as Pterocarpus macrocarpus and Xylia xylocarpa var. kerrii preferred higher elevations and drier sites compared to dry evergreen species such as Dipterocarpus alatus. Early colonizing species such as Trema orientalis and Ficus species exhibited rapid population decreases, whereas climax species such as Lagerstroemia tomentosa exhibited highly successful regeneration under natural conditions. Artificial reforestation efforts may be required in areas with large disturbance, including the planting of mixed tree species to promote natural regeneration and reduce the recovery period.

A comprehensive field investigation of the dynamic break-up processes on the Chaudière River, Quebec, Canada

Abstract The Chaudière River in Quebec, Canada, is well known for its frequent ice jam flooding events. As part of a larger watershed research program, an extensive field campaign has been carried out during the 2018–2019 and 2019–2020 winter seasons to quantify the spatiotemporal characteristics of the break-up processes along the Chaudière River. The results showed that mid-winter ice jams have formed in the Intermediate Chaudière and persisted until spring break-up. Spring break-ups were initiated in the Upper Chaudière, and then, almost simultaneously, in the Intermediate and Lower Chaudière reaches. The break-up in the Intermediate Chaudière usually lasts longer than the rest of the river since the slope is much milder, and the occurrence of mid-winter ice jams has been seen to delay the ice clearing. A reach-by-reach characterization of the cumulative degree day of thawing and discharge thresholds for the onset of break-up has been identified. During the field campaign, 51 ice jams were documented together with their location, length, date of formation, and the morphological feature triggering jam formation. Break-up patterns, hydrometeorological thresholds of ice mobilization, and ice jam sites identified in this study can serve as a basis for the implementation of an early warning system.

Importance of solar radiation and the need for improved respect to Sun by Agrometeorologists

Solar radiation refers to energy produced by the Sun, some of which reaches the Earth. This is the primary energy source for most processes in the atmosphere, hydrosphere, and biosphere. Solar radiation is of crucial importance inproviding the energy source for photosynthesis. During 1973 to 1977, when I did my Ph.D. in Agroclimatology in the Iowa State University, USA, I conducted the field experiments during 1975 and 1976 on soil-plant-water relations, growth and nutrient uptake patterns of field grown soybeans under water stress at the Western Iowa Experimental Farm, Castana. During these experiments, the solar radiation was measured with a pyranometer sensor mounted on an anodized aluminimum base. Daily solar radiation values were obtained from an LI-500 integrator attached to the pyranometer sensor. The attenuation of photosynthetically active radiation (PAR) and net radiation (NRAD) in the soybean canopy was determined during the growing season by using vertical profiles of radiation and leaf-area-index values. Once I received my Ph.D., I worked at the Headquarters of the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in Hyderabad from 1977 to 1983 and at the ICRISAT Sahelian Center, Niamey, Niger from 1984 to 1996. In several field experiments in ICRISAT, the hourly values of net radiation were obtained through net radiometers mounted above the crop canopies. The growth and interception of PAR in a maize/pigeonpea intercrop and sole maize and sole pigeonpea crops grown in large plots were compared. The productivity of maize, sorghum, pigeonpea and a maize/pigeonpea intercrop in the operational research watersheds was measured in relation to the interception of PAR. In another study, it was shown that different shading ability of the crop canopies was one of the factors which determined the crop/weed competition balance and thus contributed to differential crop productivity observed in different cropping systems. Afterwards, when I worked at the World Meteorological Organization from 1996 to 2016 as the Chief of the Agricultural Meteorology Department, as the Director of the Climate Prediction and Adaptation Branch and as the Acting Secretary of the Intergovernmental Panel on Climate Change, a lot of work was done on Solar Radiation. Given all the above work on Solar Radiation, I emphasized the need for improved respect to Sun Bhagawan by Agrometeorologists at the end of this article.

Geology, Structure, Ground Temperature and Groundwater Level in Aquifer Taliks in the Shestakovka River Basin, Eastern Siberia

The objective of this study was to evaluate subaerial taliks’ geology, configuration, ground temperature and groundwater level in the continuous permafrost environment of Central Yakutia (Eastern Siberia). The study included geophysical surveys, borehole drilling and measurements of ground temperature and groundwater level variation in a talik aquifer in the Shestakovka research watershed. The talik occupies a gentle, sandy slope covered by a sparse pine forest. Its thickness varies from 3 to 17 m. The talik has several water-conducting branches along its slope. The seasonal thaw layer outside the talik and the talik itself form a single aquifer at the end of the summer. Water-saturated deposits in the talik have a temperature of about 0 °C throughout the year and do not freeze because of the constant filtration of water through the pores and convective heat transfer. Although the groundwater level is relatively close to the land surface, at a depth of just 1–3 m, it has very weak response to snowmelt and precipitation events. The maximum groundwater level occurs in February under cryogenic pressure due to deep seasonal ground freezing above the talik aquifer. Complicated relations between the landscape and the groundwater in the given geological conditions lead to the long-term existence of talik aquifers in the continuous permafrost environment.

Research on Water-Level Recognition Method Based on Image Processing and Convolutional Neural Networks

Water level dynamics in catchment-scale rivers is an important factor for surface water studies. Manual measurement is highly accurate but inefficient. Using automatic water level sensors has disadvantages such as high cost and difficult maintenance. In this study, a water level recognition method based on digital image processing technology and CNN is proposed. For achieving batch segmentation of source images, the coordinates of the water ruler region in the source image and characters’ region and the scale lines’ region on the ruler are obtained by using image processing algorithms such as grayscale processing, edge detection, and the tilt correction method based on Hough-transform and morphological operations. The CNN is then used to identify the value of digital characters. Finally, the water level value is calculated according to the mathematical relationship between the number of scale lines detected by pixel traversal in the binarized image and the value of digital characters. This method is used to identify the water levels of the water ruler images collected in the Hulu watershed of the Qilian Mountains in Northwest China. The results show that the accuracy compared with the actual measured water level reached 94.6% and improved nearly 24% compared to the template matching algorithm. With high accuracy, low cost, and easy deployment and maintenance, this method can be applied to water level monitoring in mountainous rivers, providing an effective tool for watershed hydrology research and water resources management.

A data-driven method for estimating the composition of end-members from stream water chemistry time series

Abstract. End-member mixing analysis (EMMA) is a method of interpreting stream water chemistry variations and is widely used for chemical hydrograph separation. It is based on the assumption that stream water is a conservative mixture of varying contributions from well-characterized source solutions (end-members). These end-members are typically identified by collecting samples of potential end-member source waters from within the watershed and comparing these to the observations. Here we introduce a complementary data-driven method (convex hull end-member mixing analysis – CHEMMA) to infer the end-member compositions and their associated uncertainties from the stream water observations alone. The method involves two steps. The first uses convex hull nonnegative matrix factorization (CH-NMF) to infer possible end-member compositions by searching for a simplex that optimally encloses the stream water observations. The second step uses constrained K-means clustering (COP-KMEANS) to classify the results from repeated applications of CH-NMF and analyzes the uncertainty associated with the algorithm. In an example application utilizing the 1986 to 1988 Panola Mountain Research Watershed dataset, CHEMMA is able to robustly reproduce the three field-measured end-members found in previous research using only the stream water chemical observations. CHEMMA also suggests that a fourth and a fifth end-member can be (less robustly) identified. We examine uncertainties in end-member identification arising from non-uniqueness, which is related to the data structure, of the CH-NMF solutions, and from the number of samples using both real and synthetic data. The results suggest that the mixing space can be identified robustly when the dataset includes samples that contain extremely small contributions of one end-member, i.e., samples containing extremely large contributions from one end-member are not necessary but do reduce uncertainty about the end-member composition.

Controls on decadal, annual, and seasonal concentration‐discharge relationships in the Sleepers River Research Watershed, Vermont, northeastern United States

AbstractPast studies on concentration‐discharge (C‐Q) relationships have focused on short‐term or low‐temporal resolution data. While advancing understanding of catchment processes, these studies provided limited insight on catchment response over time or to climate change. Using 15 solutes from 1992 to 2015 at Sleepers River Research Watershed, Vermont, we compared C‐Q relationships over decades, years, and seasons to elucidate controls on stream chemical variation. We applied end‐member mixing analysis (EMMA) to identify solute sources and flow path routing. EMMA identified three end‐members: near‐surface runoff (NSR), riparian groundwater, and hillslope hollow groundwater. Shifting mixing proportions of these end‐members accounted for the temporal variability of conservative (no chemical reaction en route from source to stream) solutes in streamflow. For example, an increase in NSR fraction, typical of high flow, caused flushing (increased concentrations) of NO3−, DOC, Al, and Fe, which were greatest in NSR, dilution of specific conductance and base cation, SO42−, Si, Sr, Ba, and Mn concentrations, which were greatest in the two groundwater end‐members. This behaviour is reflected in the b‐coefficient of the C‐Q relation (C = aQb), which indicates the strength of dilution (b < −0.1) and flushing (b > 0.1) effects. For conservative solutes, the b‐coefficient decreased significantly (p < 0.01) with an increase in the groundwater to NSR concentration ratio. Solutes that are conservative and have relatively constant concentrations in end‐members over time showed consistent annual C‐Q patterns over years and decades. Furthermore, the strength of dilution or flushing was stronger during the snowmelt period, when the NSR fraction peaked, than during the dormant and growing seasons. With shorter snowmelt periods and snow to rain shifts, the flushing or dilution power of snowmelt runoff will weaken and alter catchment response to climate change. These insights provide more tools for the interpretation of catchment processes and responses to climate change.

Hydrology and biogeochemistry datasets from Sleepers River Research Watershed, Danville, Vermont, USA

AbstractThe Sleepers River Research Watershed (SRRW) in Danville, Vermont, USA, was established in 1957 by the U.S Department of Agriculture, Agricultural Research Service (ARS). The 111‐km2 area was selected as a representative mixed‐land‐use upland landscape in the northeastern USA, with the objective to study fundamental hydrological processes. The U.S. Geological Survey (USGS) currently operates SRRW and is the fourth federal agency to lead it. SRRW has hosted historic research on snowmelt modelling and streamflow generation processes, and USGS has augmented this hydrological foundation with biogeochemical cycling research. This data note describes five freely available data releases in stable repositories, extending to the late 2010s, from the indicated start date: aqueous chemistry and isotopes (1991); precipitation, water temperature, and streamflow (1991); groundwater levels (1991); ground frost depth (1983); and snow depth and water equivalent (1960). USGS research at SRRW is expected to continue, and we plan to update these releases every 1–3 years.

Going with the Flow: Shifting Face-to-Face PD to Fully Online in the Era of COVID-19

Immersive professional development is often used to provide teachers first-hand experience in developing placebased curricula. Knowing this, we had carefully crafted such a professional development for our participants to learn how to engage their students in local watershed research and ecology. However, following year one of a two-year grant-funded weeklong summer professional development opportunity for teachers in the Okefenokee Swamp, a shift to online instruction occurred due to COVID-19 related travel restrictions. Although the first summer in the swamp and the successive year of follow-up with teacher participants proved successful, the shift to online asynchronous instruction proved surprisingly successful as well. Qualitative and quantitative data compared across year one and year two indicated positive outcomes, such as a self-paced, engaging experience that required outdoor activities in participants’ local area.

Representation of Bi‐Directional Fluxes Between Groundwater and Surface Water in a Bucket‐Type Hydrological Model

AbstractIn most bucket‐type hydrological models, water can only flow from the groundwater to the stream and the flux is based on the groundwater storage. However, many catchments have losing stream sections, where streamflow recharges the groundwater. We developed a formulation to represent groundwater recharge by streamwater in a bucket‐type model and tested this formulation for the Panola Mountain Research Watershed to demonstrate its function and assess its performance. The upper reach of the Panola catchment is often dry and highly affected by flow from a bedrock outcrop; further downstream the stream is perennial. We simulated streamflow with the fully lumped version of a bucket‐type model and compared it to (a) a variant with sub‐catchments to more realistically represent the low storage and quick response from the bedrock outcrop and (b) a variant that also includes the bi‐directional exchange between the groundwater and the stream. For all three model variants, we compared simulated and observed streamflow and groundwater dynamics. Although the gain in overall model performance by including the bi‐directional exchange between the groundwater and the stream was small, the explicit representation of this exchange led to better streamflow simulations during drying‐down and wetting‐up periods. For Panola the fluxes along the stream appeared less important than subsurface drainage from the upper sub‐catchment to the downstream sub‐catchment. We recommend considering the bi‐directional fluxes between groundwater and the stream in bucket‐type hydrological models where these processes are important, and the focus of the simulations is on low flow conditions.

The USDA‐Agricultural Research Service's long term agro‐ecosystems Walnut Gulch Experimental Watershed, Arizona, USA

AbstractThe Walnut Gulch Experimental Watershed (WGEW) is one of the premier semiarid research watersheds in the world. This data note provides background and an overview of the watershed, data collected on the watershed, and citations and links to detailed descriptions of the instruments methods to make the observations. The long title of the dataset is: USDA‐ARS WGEW Database curated by the USDA‐Agricultural Research Service's (ARS) Southwest Watershed Research Center.

Studi Pemisahan Aliran Dasar Metode Local Minimum Method Daerah Aliran Sungai Miu

The two main elements of a river flow hydrograph are direct runoff and baseflow. Base flow is a flow that comes from groundwater and it is available during the rainy and dry seasons. Information of baseflow value of a watershed has an important meaning in efforts to develop and manage water resources, including the provision of clean water, irrigation systems, flood management and others. Miu watershed located in Sigi Regency often experiences natural disasters such as floods and droughts that occur almost every year, which is the research location with an area of 65,452.01 Ha. This study aims to determine the value of baseflow using the Local Minimum Method and to find out whether this method can be used for baseflow modeling in research watersheds. This study was conducted using Hydro Office software with input data in the form of daily discharge data from 2004 to 2013. The average baseflow value obtained was 5.43 m3/s. The process of calibrating the baseflow value by taking flow data in the dry season where there is no rainfall input. It is obtained that BFI have value an average of 0.89. This value indicates that the Miu watershed has high storage permeability characteristics, The Miu watershed has quite stable flow during dry periods, because the greater the BFI value, the better the water supply in a watershed. In the statistical test, the observed discharge is the discharge data from the measurement results for the period 2004-2013, while the calculated discharge is the result of the estimated base flow value obtained using the graphical method. From the results of the statistical test of RMSE and R2, the RMSE value was 0.147 and the R2 value was 0.751. Both statistical tests show that the local minimum method has a fairly good performance in modeling the base flow in the Miu watershed.

Detailed streamflow data for understanding hydrologic responses in the Logan River Observatory

AbstractThe Logan River watershed, located in Northern Utah, USA, consists of a relatively pristine, mountainous area that drains to a lower elevation, valley area influenced by both urban development and agriculture. The Logan River Observatory has been collecting aquatic (streamflow and water quality) and climate data throughout the Logan River watershed since 2014. While streamflow measurements are commonly made at the outlets of research watersheds, the Logan River watershed consists of diverse hydrologic, topographic, and geologic settings that require a detailed understanding of streamflow variability over time at many locations. Here, we illustrate: (a) the importance of collecting streamflow time series throughout complex watersheds, and (b) how simple flow balances can provide much needed hydrologic insight into the locations and timing of gains and losses over reaches to guide future investigations.

Little River Experimental Watershed, a keystone in understanding of coastal plain watersheds

AbstractThe US Department of Agriculture‐Agricultural Research Service Southeast Watershed Research Laboratory (SEWRL) initiated a hydrologic research program on the Little River Experimental Watershed (LREW) in 1967. Long‐term (52 years) streamflow data are available for nine sites, including rainfall‐runoff relationships and hydrograph characteristics regularly used in research on interactive effects of climate, vegetation, soils, and land‐use in low‐gradient streams of the US EPA Level III Southeastern Plains ecoregion. A summary of prior research on the LREW illustrates the impact of the watershed on building a regional understanding of hydrology and water quality. Climatic and streamflow data were used to make comparisons of scale across the nine nested LREW watersheds (LRB, LRF, LRI, LRJ, LRK, LRO, LRN, LRM, and LRO3) and two regional watersheds (Alapaha and Little River at Adel). Annual rainfall for the largest LREW, LRB, was 1200 mm while average annual streamflow was 320 mm. Annual rainfall, streamflow, and the ratio between annual streamflow and rainfall (Sratio) were similar (α = 0.05) across LREWs LRB, LRF, LRI, LRJ, LRK, and LRO. While annual rainfall within the 275 ha LRO3 was found to be similar to LRO and LRM (α = 0.05), annual streamflow and Sratio were significantly different (α = 0.05). Comparisons of annual rainfall, streamflow, and Sratio between LRB and the regional watersheds indicated no differences (α = 0.05). Based upon this analysis, most regional watersheds shared similar hydrologic characteristics. LRO3 was an exception, where increases in row crops and decreases in forest coverage resulted in increased streamflow. LREW data have been instrumental in building considerable scientific understanding of flow and transport processes for these stream systems. Continued operation of the LREW hydrologic network will support hydrologic research as well as environmental quality and riparian research programs that address emerging and high priority natural resource and environmental issues.

Drivers of Dissolved Organic Carbon Mobilization From Forested Headwater Catchments: A Multi Scaled Approach

Understanding and predicting catchment responses to a regional disturbance is difficult because catchments are spatially heterogeneous systems that exhibit unique moderating characteristics. Changes in precipitation composition in the Northeastern U.S. is one prominent example, where reduction in wet and dry deposition is hypothesized to have caused increased dissolved organic carbon (DOC) export from many northern hemisphere forested catchments; however, findings from different locations contradict each other. Using shifts in acid deposition as a test case, we illustrate an iterative “process and pattern” approach to investigate the role of catchment characteristics in modulating the steam DOC response. We use a novel dataset that integrates regional and catchment-scale atmospheric deposition data, catchment characteristics and co-located stream Q and stream chemistry data. We use these data to investigate opportunities and limitations of a pattern-to-process approach where we explore regional patterns of reduced acid deposition, catchment characteristics and stream DOC response and specific soil processes at select locations. For pattern investigation, we quantify long-term trends of flow-adjusted DOC concentrations in stream water, along with wet deposition trends in sulfate, for USGS headwater catchments using Seasonal Kendall tests and then compare trend results to catchment attributes. Our investigation of climatic, topographic, and hydrologic catchment attributes vs. directionality of DOC trends suggests soil depth and catchment connectivity as possible modulating factors for DOC concentrations. This informed our process-to-pattern investigation, in which we experimentally simulated increased and decreased acid deposition on soil cores from catchments of contrasting long-term DOC response [Sleepers River Research Watershed (SRRW) for long-term increases in DOC and the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO) for long-term decreases in DOC]. SRRW soils generally released more DOC than SSHCZO soils and losses into recovery solutions were higher. Scanning electron microscope imaging indicates a significant DOC contribution from destabilizing soil aggregates mostly from hydrologically disconnected landscape positions. Results from this work illustrate the value of an iterative process and pattern approach to understand catchment-scale response to regional disturbance and suggest opportunities for further investigations.

Approaching four decades of forest watershed research at Upper Penticton Creek, British Columbia: A synthesis

AbstractOver the past 35 years, the Upper Penticton Creek (UPC) Watershed Experiment has supported forest hydrology research in south‐central British Columbia (BC), Canada. This paper provides a synthesis of research results, highlights the challenges facing UPC and identifies new research directions. Clearcutting approximately 50% of two small, snow‐dominated (Dfb Koppen classification) watersheds advanced the timing of snowmelt‐generated high flows and decreased late‐summer low flows, relative to predictions based on pre‐treatment regressions. Changes in high flows did not have a significant effect on stream channels due to low stream power, coarse substrate, and limited riparian disturbance. Changes in summer low flows reduced modelled useable fish habitat by 20%–50%. Evaporation averaged 52% of the annual precipitation in the mature forest, was reduced to 30% in a clearcut, and recovered to 40% and 47% in a 10 and 25 year‐old stand, respectively. Groundwater recharge to the bedrock was estimated at 19% of annual precipitation, indicating that, even with the large uncertainty associated with this estimate, deep groundwater should not be ignored in the water balance. Suspended sediment, turbidity, and colour increased post‐logging; however, chemical surface water quality did not change. Aquatic community structure changed post‐logging; and although this affected the processing of organic matter, the effects on habitat quality were considered minimal. The information gained at UPC has supported provincial policies, management guidelines, forest stewardship plans and watershed risk assessments. The undisturbed control watershed, re‐growing treatment watersheds and ongoing long‐term hydrometric monitoring continue to provide opportunities for future research addressing issues such as the effects of young forests on streamflow and hydrologic recovery, and the influence of climate change on the hydrologic regime.

The evolving perceptual model of streamflow generation at the Panola Mountain Research Watershed

AbstractThe Panola Mountain Research Watershed (PMRW) is a 41‐hectare forested catchment within the Piedmont Province of the Southeastern United States. Observations, experimentation, and numerical modelling have been conducted at Panola over the past 35 years. But to date, these studies have not been fully incorporated into a more comprehensive synthesis. Here we describe the evolving perceptual understanding of streamflow generation mechanisms at the PMRW. We show how the long‐term study has enabled insights that were initially unforeseen but are also unachievable in short‐term studies. In particular, we discuss how the accumulation of field evidence, detailed site characterization, and modelling enabled a priori hypotheses to be formed, later rejected, and then further refined through repeated field campaigns. The extensive characterization of the soil and bedrock provided robust process insights not otherwise achievable from hydrometric measurements and numerical modelling alone. We focus on two major aspects of streamflow generation: the role of hillslopes (and their connection to the riparian zone) and the role of catchment storage in controlling fluxes and transit times of water in the catchment. Finally, we present location‐independent hypotheses based on our findings at PMRW and suggest ways to assess the representativeness of PMRW in the broader context of headwater watersheds.