A regional suspended load yield estimation model for ungauged watersheds

Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield(SLY)in ungauged watersheds. However, using all the variables might reduce the applicability of these models. Therefore, data reduction techniques(DRTs), e.g., principal component analysis(PCA), Gamma test(GT), and stepwise regression(SR), have been used to select the most effective variables. The artificial neural network(ANN) and multiple linear regression(MLR) are also common tools for SLY modeling. We conducted this study(1) to obtain the most effective variables influencing SLY through DRTs including PCA, GT, and SR, and then, to use them as input data for ANN and MLR; and(2) to provide the best SLY models. Accordingly, we used 14 physiographic, climatic, and hydrologic parameters from 42 watersheds in the Hyrcanian forest region(in northern Iran). The most effective variables as determined through DRTs as well as the original data sets were used as the input data for ANN and MLR in order to provide an SLY model. The results indicated that the SLY models provided by ANN performed much better than the MLR models, and the GT-ANN model was the best. The determination of coefficient,relative error, root mean square error, and bias were 99.9%, 26%, 323 t/year, and 6 t/year in the calibration period, and 70%, 43%, 456 t/year, and 407 t/year in the validation period, respectively. Overall, selecting the main factors that influence SLY and using artificial intelligence tools can be useful for water resources managers to quickly determine the behavior of SLY in ungauged watersheds.

Reduction of the wind erosion potential in dried-up lakebeds using artificial biocrusts

The artificial creation of biocrusts can be a rapid and pervasive solution to reduce wind erosion potential(WEP)in dried-up lakes(e.g.,Lake Urmia).So,in this study,we created a biocrust by the inoculation of bacteria and cyanobacteria on trays filled by soils collected from the dried-up bed of Lake Urmia,Iran,to reduce WEP in laboratory conditions.We used the wind erodible fraction of soil(EF)and soil crust factor(SCF)equations to calculate the WEP of the treated soils.EF and SCF were decreased(p<0.05)through applying the co-inoculation of bacteria and cyanobacteria by 5.6%and 10.57%,respectively,as compared to the control;also,the"cyanobacteria alone"inoculation decreased EF by 3.9%.Our results showed that the artificial biocrusts created by soil inoculation,especially with the co-using of bacteria and cyanobacteria,significantly reduced the WEP of a newly dried-up lakebed.Furthermore,we found that inoculation decreased the WEP of the study soil by increasing the soil organic matter content from 3.7 to 5 fold.According to scanning electron microscopy images,the inoculated microorganisms,especially cyanobacteria,improved soil aggregation by their exopolysaccharides and filaments;thus,they can be used with other factors to estimate the soil erodibility in well-developed biocrusts.The inoculation technique could be considered as a rapid strategy in stabilizing lakebeds against wind force.However,it should be confirmed after additional experiments using wind tunnels under natural conditions.

Effects of type, level and time of sand and gravel mining on particle size distributions of suspended sediment

Monitoring the sediment transport behavior induced by different interventions, particularly sand mining from rivers, is needed to adaptively manage the watersheds. The particle size distribution of the sus-pended sediment in up and downstream of rivers is one of the main indicators to know about fate of sediments, which may be varied in different conditions. We investigated the effect of some types of sand and gravel (i.e., manual and low, semi-heavy, and heavy machinery) mining on particle size distribution of suspended sediment in the Vaz-e-Owlya, Vaz-e-Sofla and Alesh-Roud riverine mines located in Ma-zandaran Province, northern Iran. The study was conducted on a monthly basis from February, 2012 to January, 2013. Laser granulometry was used to analyze the particle size distribution of suspended se-diment samples taken from up and downstream sections of the study mines. The results revealed that the level and intensity of mining activity affected particle size distribution of suspended sediments. Further statistical assessments in up and downstream sections of the mines proved that sorting, D50, mean, D90, kurtosis, skewness and D10 of the suspended sediment were not significantly influenced by mining activities at levels of 0.09, 0.11, 0.12, 0.15 to 0.69, 0.15–0.69, 0.77, 0.87, 0.97, respectively. While it was not statistically significant, we found that the type of mine and the level of the exploitation changed the particle size distribution of the suspended sediment.