soroush namjoofar; Ahmad Nohegar; Zeinab Sazvar
Abstract
Horul Azim Wetland is located in the southwestern Iran in Khuzestan Province, has 1180 km2. About 70% of the wetland is located in Iraq, which has faced the challenges of drought and oil drilling, and many of its southern lands have dried up and become dust center. The present study was conducted with ...
Read More
Horul Azim Wetland is located in the southwestern Iran in Khuzestan Province, has 1180 km2. About 70% of the wetland is located in Iraq, which has faced the challenges of drought and oil drilling, and many of its southern lands have dried up and become dust center. The present study was conducted with the aim of assessing the levels of heavy metal pollution in the dried part of this wetland. At first, 15 stations were identified on the LANDSAT image and the dried soil of the wetland was sampled by quadrat and the Cd, Cu, Pb, Fe, Mn and Ni were measured by ICP-MS device. To assess the pollution levels, Igeo, ER, PLI, RI, CSI and mCd were used. The results showed that the concentration of Cd, Cu, Ni and Pb is higher than the shale standard. According to the Igeo, Cd pollution is high (moderate to severe). According to the PI, Cd and Pb pollution are high and moderate, respectively. The ER shows that the ecological pollution of Cd is significant, but other metals don't have ecological risk. The average of the cumulative indices ER and PLI were 193 and 9.7, respectively, indicating a possible ecological risk for all points. The CSI pollution safety for Cd, Cu, Ni and Pb was 0.52, 0.25, 4.02 and 0.34, and the mCd index was 0.27, 10.4, 13.9 and 8.9, respectively, indicating a very high severity of pollution safety for Ni and Cd.
mahboobeh moatamednia; ahmad nohegar; arash malekian; maryam saberi anari
Abstract
One of the most important of hydrological computing in ecosystem is estimation of the relationship between rainfall and runoff. So that investigation occurred processes in it and the estimate of important outputs such as flood and sediment is considered one the most important mission of a watershed project. ...
Read More
One of the most important of hydrological computing in ecosystem is estimation of the relationship between rainfall and runoff. So that investigation occurred processes in it and the estimate of important outputs such as flood and sediment is considered one the most important mission of a watershed project. Because of variable spatial and temporal characteristics of incident in the water cycle and the nonlinear relationship and uncertainties, none of the statistical and conceptual models are able to be a better and capable model for that. But today using nonlinear networks as intelligent system for forecasting such complicated event can be efficient and effective in many problems of ecology. For this aim it is used variables such as precipitation, temperature, evartanspiration, relative humidity and discharges in daily scale over 42 years period and assessment 62 different suggested structures for surveying river flow in Amame representative watershed. For comparison it used Multi Layer Perceptoron (MLP) and Radial Basis Function (RBF).The results show that out of 6000 available models for estimation river flow model number 54 with 8-9-8-1 network structure and 8 types of input variable such as precipitation (Pt), precipitation with two lags (Pt-1 and Pt-2), temperature (Tt), evartanspiration (ETt), relative humidity (Rht), and discharge with two lags (Qt-1 and Qt-2) with Multi Layer Perceptoron method has the best function. The error of model was 0.03, 0.18 and 0.04 in training and 0.02, 0.14 and 0.02 for testing stage for MSE, RMSE and MAE, respectively.
