Jeff A. Hatten

The effects of wildfire on the sediment yield of a coastal California watershed

The occurrence of two wildfi res separated by 31 yr in the chaparral-dominated Arroyo Seco watershed (293 km 2 ) of California provides a unique opportunity to evaluate the effects of wildfi re on suspended-sediment yield. Here, we compile discharge and suspended-sediment sampling data from before and after the fi res and show that the effects of the postfi re responses differed markedly. The 1977 Marble Cone wildfi re was followed by an exceptionally wet winter, which resulted in concentrations and fl uxes of both fi ne and coarse suspended sediment that were ~35 times greater than average (sediment yield during the 1978 water year was 11,000 t/km 2 /yr). We suggest that the combined 1977–1978 fi re and fl ood had a recurrence interval of greater than 1000 yr. In contrast, the 2008 Basin Complex wildfi re was followed by a drier than normal year, and although suspended-sediment fl uxes and concentrations were signifi cantly elevated compared to those expected for unburned conditions, the sediment yield during the 2009 water year was less than 1% of the post–Marble Cone wildfi re yield. After the fi rst postfi re winters, sediment concentrations and yield decreased with time toward prefi re relationships and continued to have signifi cant rainfall dependence. We hypothesize that the differences in sediment yield were related to precipitationenhanced hillslope erosion processes, such as rilling and mass movements. The millennialscale effects of wildfi re on sediment yield were explored further using Monte Carlo simulations, and these analyses suggest that infrequent wildfi res followed by flincrease long-term suspended-sediment fl markedly. Thus, we suggest that the current approach of estimating sediment yield from sediment rating curves and discharge data— without including periodic perturbations from wildfi res—may grossly underestimate actual sediment yields.

Fire severity effects on soil organic matter from a ponderosa pine forest: a laboratory study

This study investigated the changes in soil organic matter composition by controlling fire severity of laboratory burns on reconstructed surface soil profiles (O, A1 (0–1 cm), and A2 (1–2 cm)). Laboratory burning simulated prescribed burns that would be typical in the understorey of a ponderosa pine forest at low, moderate, and high–moderate severity levels. Soils were analysed for C, N and soil organic matter composition. Soil organic matter was fractionated into humin, humic acid, fulvic acid, soluble non‐humic materials and other hydrophobic compounds. In the O horizon, low‐, moderate‐, and high‐severity treatments consumed an increasing proportion of C and N. Carbon content of the mineral soil was unaffected by burning; however, N content of the A2 horizon decreased after the moderate‐ and high‐severity treatments, likely as a result of N volatilisation. The proportion of non‐soluble material in the O horizon increased with fire severity, whereas the proportion of humin C as total C of the A horizon decreased with fire severity. The decrease in humin was followed by an increase in the other hydrophobic compounds. The higher fire intensity experienced by the burning O horizon created recalcitrant materials while an increase in labile soil organic matter was observed in mineral soil. An increase in labile soil organic matter may cause elevated C and N mineralisation rates often seen after fire.

A STELLA model to estimate soil CO 2 emissions from a short-rotation woody crop

The potential for climatic factors as well as soil–plant–climate interactions to change as a result of rising levels of atmospheric CO2 concentration is an issue of increasing international environmental concern. Agricultural and forest practices and managements may be important contributors to mitigating elevated atmospheric CO2 concentrations. A computer model was developed using the Structural Thinking and Experiential Learning Laboratory with Animation (STELLA) software for soil CO2 emissions from a short-rotation woody crop as affected by soil water and temperature regimes, root and microbial respiration, and surficial processes such as rainfall, irrigation, and evapotranspiration. The resulting model was validated with good agreement between the model predictions and the experimental measurements prior to its applications. Two scenarios were then chosen to estimate both diurnal and annual soil CO2 emissions from a 1-ha mature cottonwood plantation as affected by soil temperature, soil (i.e., root and microbial) respiration, and irrigation. The simulation resulted in typical diurnal soil respiration and CO2 emission patterns, with increases from morning to early afternoon and decreases from early afternoon to midnight. This pattern was driven by diurnal soil temperature variations, indicating that soil temperature was the main influence on soil respiration and CO2 efflux into the atmosphere. Our simulations further revealed that the average seasonal soil respiration rate in summer was 1.6 times larger than in winter, whereas the average seasonal CO2 emission rate in summer was 1.77 times larger than in winter. Characteristic annual variation patterns for soil respiration and CO2 emission also were modeled, with both increasing from January 1 through June 30 followed by steady declines from September 1 through December 31. These results suggest that the STELLA model developed is a useful tool for estimating soil CO2 emission from a short-rotation woody crop plantation.

Real-time estimation of TP load in a Mississippi Delta stream using a dynamic data driven application system.

Elevated phosphorus (P) in surface waters can cause eutrophication of aquatic ecosystems and can impair water for drinking, industry, agriculture, and recreation. Currently, no effort has been devoted to estimating real-time variation and load of total P (TP) in surface waters due to the lack of suitable and/or cost-effective wireless sensors. However, when considering human health, drinking water supply, and rapidly developing events such as algal blooms, the availability of timely P information is very critical. In this study, we developed a new approach in the form of a dynamic data driven application system (DDDAS) for monitoring the real-time variation and load of TP in surface water. This DDDAS consisted of the following three major components: (1) a User Control that interacts with Schedule Run to implement the DDDAS with starting and ending times; (2) a Schedule Run that activates the Hydstra model; and (3) a Hydstra model that downloads the real-time data from a US Geological Survey (USGS) website that is updated every 15 min with data from USGS monitoring stations, predicts real-time variation and load of TP, graphs the variables in real-time on a computer screen, and sends email alerts when the TP exceeds a certain value. The DDDAS was applied to monitor real-time variation and load of TP for 30 days in Deer Creek, a stream located east of Leland, Mississippi, USA. Results showed that the TP concentrations in the stream ranged from 0.24 to 0.48 mg L(-1) with an average of 0.30 mg L(-1) for a 30-day monitoring period, whereas the cumulative load of TP from the stream was about 2.8 kg for the same monitoring period. Our study suggests that the DDDAS developed in this study was useful for estimating the real-time variation and load of TP in surface water ecosystems.

Conversion to drip irrigated agriculture may offset historic anthropogenic and wildfire contributions to sediment production

This study is an investigation into the roles of wildfire and changing agricultural practices in controlling the inter-decadal scale trends of suspended sediment production from semi-arid mountainous rivers. In the test case, a decreasing trend in suspended sediment concentrations was found in the lower Salinas River, California between 1967 and 2011. Event to decadal scale patterns in sediment production in the Salinas River have been found to be largely controlled by antecedent hydrologic conditions. Decreasing suspended sediment concentrations over the last 15years of the record departed from those expected from climatic/hydrologic forcing. Sediment production from the mountainous headwaters of the central California Coast Ranges is known to be dominated by the interaction of wildfire and large rainfall/runoff events, including the Arroyo Seco, an ~700km(2) subbasin of the Salinas River. However, the decreasing trend in Salinas River suspended sediment concentrations run contrary to increases in the watersheds effective burn area over time. The sediment source area of the Salinas River is an order of magnitude larger than that of the Arroyo Seco, and includes a more complicated mosaic of land cover and land use. The departure from hydrologic forcings on suspended sediment concentration patterns was found to coincide with a rapid conversion of irrigation practices from sprinkler and furrow to subsurface drip irrigation. Changes in agricultural operations appear to have decreased sediment supply to the Salinas River over the late 20th to early 21st centuries, obscuring the influence of wildfire on suspended sediment production.

Evaluating hydrologic effect of forest harvesting at Upper Pearl River Watershed in Mississippi

Forest harvesting activities can have significant impact on watershed hydrological processes and water quality. Sedimentation due to forest harvesting has been identified as one of the major threat to Upper Pearl River Watershed (UPRW) located in east central Mississippi. The overall objective of this study was to evaluate the impact of forest harvesting, particularly clear cutting and thinning, on hydrological and water quality characteristics at UPRW. The Soil and Water Assessment Tool (SWAT) model was used to assess hydrologic impacts such as flow, surface runoff and water yields, and water quality effect such as sediment yield.

A simple approach to estimate daily loads of total, refractory, and labile organic carbon from their seasonal loads in a watershed

Loads of naturally occurring total organic carbons (TOC), refractory organic carbon (ROC), and labile organic carbon (LOC) in streams control the availability of nutrients and the solubility and toxicity of contaminants and affect biological activities through absorption of light and complex metals with production of carcinogenic compounds. Although computer models have become increasingly popular in understanding and management of TOC, ROC, and LOC loads in streams, the usefulness of these models hinges on the availability of daily data for model calibration and validation. Unfortunately, these daily data are usually insufficient and/or unavailable for most watersheds due to a variety of reasons, such as budget and time constraints. A simple approach was developed here to calculate daily loads of TOC, ROC, and LOC in streams based on their seasonal loads. We concluded that the predictions from our approach adequately match field measurements based on statistical comparisons between model calculations and field measurements. Our approach demonstrates that an increase in stream discharge results in increased stream TOC, ROC, and LOC concentrations and loads, although high peak discharge did not necessarily result in high peaks of TOC, ROC, and LOC concentrations and loads. The approach developed herein is a useful tool to convert seasonal loads of TOC, ROC, and LOC into daily loads in the absence of measured daily load data.