Sustainable use of soil resources can be assessed from management‐induced changes in soil properties from long‐term experiments. Such data are scanty, especially with regard to changes in soil physical properties. Therefore, soil physical and chemical analyses were performed 28 yr after initiating a crop rotation‐tillage experiment on a well‐drained Wooster silt loam soil (fine‐loamy, mixed, mesic Typic Fragiudalf) at Wooster, OH. All combinations of three rotations (continuous corn [CC; Zea mays L.]; corn and soybean [Glycine max (L.) Merr.] in a 2‐yr rotation [CS]; and corn, oat [Avena sativa L.], and meadow in a 3‐yr rotation [COM]) and of three tillage treatments (no‐tillage [NT]; chisel plow [CP]; and moldboard plow [MP]) were maintained on the same plots for the entire length of study. All crops were grown every year. Soil properties studied for the 0‐ to 15‐cm layer were: structural stability of aggregates, bulk density, total porosity, penetration resistance, organic C, pH, cation‐exchange capacity (CEC), and exchangeable K, Ca and Mg. Mean bulk densities measured prior to tillage treatments and planting were 1.18, 1.24, and 1.28 Mg m−3 for CC, CS, and COM rotations, respectively. The lowest bulk density was observed for the CC‐NT combination. Total aggregation in CS was 26.9% greater than CC and 111.2% greater than COM. With tillage treatments, aggregation was in the order of NT>CP>MP. Rotation treatments had no effect on aggregate size. In accord with bulk density, the relative magnitude of organic C content was 100, 85, and 63 for CC, CS, and COM rotations, respectively.

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There are different approaches to define the soil available water (SAW) for plants. The objectives of this study are to evaluate the SAW values of 12 arable soils from Hamadan province (western Iran) calculated by plant available water (PAW), least limiting water range (LLWR) and integral water capacity (IWC) approaches and to explore their relations with Dexter's index of soil physical quality (i.e., S-value). Soil water retention and mechanical resistance were determined on the intact samples which were taken from the 5-10 cm layer. For calculation of LLWR and IWC, the van Genuchten-Mualem model was fitted to the observed soil water retention data. Two matric suctions (h) of 100 and 330 cm were used for the field capacity (FC). There were significant differences (P<0.01) between the SAW values calculated by PAW 100 , PAW 330 , LLWR 100 , LLWR 330 and IWC. The highest (i.e., 0.210 cm 3 cm −3 ) and the lowest (i.e., 0.129 cm 3 cm −3 ) means of SAW were calculated for the IWC and LLWR 330 , respectively. The upper limit of LLWR 330 for all of the soils was h of 330 cm, and that of LLWR 100 (except for one soil that was airfilled porosity of 0.1 cm 3 cm −3 ) was h of 100 cm. The lower limit of LLWR 330 and LLWR 100 for five soils was h of 15,000 cm and for seven soils was mechanical resistance of 2 MPa. The IWC values were smaller than those of LLWR 100 for two soils, equal to those of LLWR 100 for three soils and greater than those of LLWR 100 for the rest. There is, therefore, a tendency to predict more SAW using the IWC approach than with the LLWR approach. This is due to the chosen critical soil limits and gradual changes of soil limitations vs. water content in the IWC calculation procedure. Significant relationships of SAW with bulk density or relative bulk density were found but not with the clay and organic matter contents. Linear relations between IWC and LLWR 100 or LLWR 330 were found as: IWC=−0.0514 + 1.4438LLWR 100 , R 2 = 0.83; and IWC=−0.0405 + 2.0465LLWR 330 , R 2 =0.84, respectively (both significant at P<0.01). Significant relationships were obtained between the SAW values and S indicating the suitability of the index S to explain the availability of soil water for plants even when complicated approaches like IWC are considered. Overall, the results demonstrate the importance of the choice of the approach to be used and its critical limits in the estimation of the soil available water to plants.

Abstract:Dye tracing field data were collected in small, steep streams in Ontario and used to calculate longitudinal dispersion coefficients for these headwater streams. A predictive equation for longitudinal dispersion coefficient is developed using combined data sets from five steeper head -water streams and 24 milder and larger rivers. The predictive equation relates the longitudinal dispersion coefficient to hydraulic and geometric parameters of the stream and has been developed using multiple regression analysis. The newly developed equation shows impressive accuracy of predictions for longitudinal dispersion coefficient (R 2 = 0.86, RMSE = 25, Nash-Sutcliffe coefficient E ns = 0.86 and Index of Agreement D = 0.96) for both small, steep headwater streams as well as large, mild rivers. The Froude number has been introduced as a third key parameter to capture the effect of slope of the reach -in addition to the aspect ratio and bed material surface roughness -on the longitudinal dispersion coefficient. The pronounced improvement in the accuracy of the prediction is due to the addition of the Froude number to capture the effect of the slope of the reach on longitudinal dispersion coefficient.