Khaled Osati; Hamed Joneidi; Nahid Azizi
Abstract
Prediction of rangeland species forage yield is one of the most effective tools for planning and policymaking of natural resources in each country. Climate variables (precipitation and temperature) play an important role in forecasting rangeland species production. In the present study, the forages yields ...
Read More
Prediction of rangeland species forage yield is one of the most effective tools for planning and policymaking of natural resources in each country. Climate variables (precipitation and temperature) play an important role in forecasting rangeland species production. In the present study, the forages yields of some typical species in Ghoosheh rangeland, Semnan, measured using cutting and weighing method. It was evaluated in 30 plots with an area of two square meter, distributed along with two transect lines, for a 10-year period (water year 2005-2006 to 2014-2015), to determine the effects of drought on the forages yield of typical species in the studied areas. In the next step, several drought indices were calculated. The relationship between forages yield of rangeland species and drought indices values investigated to model forages production of study areas via drought indices. According to the values of drought indices SIAP, PNPI and Z-Score, several drought and wet-year periods occurred during the assessed 10-year. The relationship between forages production and drought indices confirmed that the best simple linear regression model for estimating total forages production of studied area was introduced by SIAP and Z-Score indices (RRMSE = 0.1) explaining 53% of production changes at 95% confidence level. The effects of drought and wet-year periods varied among different species so as to the annual production varied greatly for annual species (between 1 and 11% of total annual forages yield) and slightly for perennials and shrubs.
Khaled Osati; Ali Salajegheh; Mohammad Mahdavi; Paul Koeniger; Kamran Chapi; Arash Malekian
Abstract
Within the climate change debate and its probable impacts on water resources systems, design and operation of management plans based on the assumption of stationary hydrology may cause serious challenge to accurately predict future supplies. Therefore this case study is trying to assess trend in hydroclimatic ...
Read More
Within the climate change debate and its probable impacts on water resources systems, design and operation of management plans based on the assumption of stationary hydrology may cause serious challenge to accurately predict future supplies. Therefore this case study is trying to assess trend in hydroclimatic variables of Karkheh Rivers upstream by applying modified Mann-Kendall trend test on long term daily time series of temperature, precipitation and discharge. Temperature variables are mostly showing meaningful increasing trends but observed changes in assessed stations were not spatially uniform for precipitation. Streamflow variables depict a decreasing trend, though more noticeable in base flows. Decreasing trend is meaningful for annual discharge median in Holailan at 90% confidence level. Total yearly precipitation, number of precipitation days and number of days with precipitation equal to, or greater than, 10 mm/d show the most correlation with stream flow variables. Comparing monthly discharge with temperature and precipitation variables in the studied gages indicates a time-delay in system response to inputs. This may related to snowmelt contributions or contributions of water into streams after passing through different hydrological pathways such as groundwater. Some parts of streamflow changes, especially about base flows, is not completely verified by precipitation changes and can be attributed to changes in temperature or another factors such as groundwater overexploitation.
Kh. Osati; A. Salajegheh; S. Arekhi
Abstract
Spatiality assessment of groundwater pollution is very important to determine water quality condition, pollution sources and management decisions. In this case, GIS and geostatistics methods can be useful tools. Spatiality of groundwater quality parameters, in relation with various land uses, can be ...
Read More
Spatiality assessment of groundwater pollution is very important to determine water quality condition, pollution sources and management decisions. In this case, GIS and geostatistics methods can be useful tools. Spatiality of groundwater quality parameters, in relation with various land uses, can be very extremely. Therefore water samples from 52 wells in the Kurdan area were analyzed in this study. The results show that nitrate concentrations are less than maximum acceptable concentration in drinking water (i.e. 50 mg/L as nitrate recommended by ISIRI and WHO guideline values) except to one sample (2 percent of samples) in the study area. Various geostatistics methods, e.g. IDW (power 1-4), ordinary Kriging and RBF (five Kernel functions) were compared after assessing the variograms and the spatiality of nitrate samples. Then the model parameters were calibrated and through the specific methods, predicted and standard errors maps were prepared. Errors criteria show that Kriging is the best fitting model in the study area. Finally, probability map of NO3 concentrations exceeding the threshold value of 50 mg/L, is generated using the Indictor Kriging method. Spatiality of NO3 show that Nitrate concentration is increased where the rock type is permeable, land use is agriculture and slope is enough low to infiltrate polluted water into the wells. This research also tries to describe how to assess the spatiality of groundwater parameters by GIS.
