JWSS - Journal of Water and Soil Science

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A number of researches have indicated a gradual increase in mean temperature throughout the world. Yet, there are some reports on the reduction of annual mean temperature. In this research we investigated a long-term trend of annual mean temperature in 34 synoptic stations in Iran (2 stations in cold and humid climates 14 in humid and moderate climates, 11 in Steppe climate and 7 in desert climate - following Kopen climatic division) with a minimum statistical record of 30 years by applying the minimum square-error and Man-Kendall methods (Wald-Wolfowitz method had a different result). The results confirmed a positive trend in 59% stations, while 41 % of the stations were negative for the whole time-horizon of data. Considering the significance level, 3 zones of positive, negative, and no trends for annual mean temperature were detected in Iran. However, it was hard to define a specific spatial theme for such a division. By taking another approach, we proceeded with a shared statistical time period of 1968-1998 for all stations. In this case, 68% of the stations showed a positive trend, while the remaining 32% was negative. There were some shifts in direction from one trend to another in some of the stations in the study, yet no well-defined spatial structure was reported. In contrast, at 5% level of significance, 44, 15 and 41 percentages of the stations demonstrated positive, negative, and no trend for annual mean temperature, respectively. In general the behavior was different for different climates and no specific pattern was found. So, despite the fact that some stations did not show significant trends, one may hypothesize that more regions in future will experience higher temperature values and their positive trends would be a clue for future warming.

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In this study the impact of climate change on temperature, rainfall and river flows of the Zayandeh Rud basin under two climate change scenarios for two periods (2010-2039 and 2070-2099) are investigated. For the evaluation of future climate change impact on stream flow to Chadegan reservoir, the global circulation model (GCM) outputs of the HadCM3 model (monthly temperature and precipitation) with two scenarios, A2 and B2, are obtained and downscaled to the local level for the selected time periods. The results indicate that the annual average of precipitation decreases and temperature increases for both periods that are more pronounced for the period 2079-2099. Such that 10% to 16% decrease in precipitation and 3.2 to 4.6ºC increases in temperature can be anticipated for scenarios A2 and B2, respectively. To predict future stream flow changes due to climate change, artificial neural networks (ANNs) have been applied and trained by the several input models and architectures for rainfall-runoff simulation. The results indicate that the maximum of 5.8% decrease in the annual flows. Comparison of the two scenarios indicates the more critical situation in scenario A2 for the basin.

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The effect of overgrazing on vegetation changes in central Zagros has been studied by a few scientists, but there is no detailed information on the impact of such practices on soil properties. The objective of this study was to assess the effect of climate and grazing management on selected soil biochemical properties. Fourteen experimental range sites protected against grazing as well as their adjacent overgrazed sites in Chadegan, Pishkuh and Poshtkuh were selected. In each site, samples were collected from the depths 0-5 and 5-15 cm. Soil organic C (OC), microbial biomass C (MBC), total nitrogen (TN), organic C to total N ratio (C/N), microbial biomass C to organic C ratio (C_mic/C_oc) and metabolic quotient (qCO2) were measured and/or calculated. The results showed that the lowest SOC, MBC, TN and Cmic/Coc occur in Chadegan due to low fresh materials input. The above parameters in Pishkuh and Poshtkuh regions are 2.5 to 3 times greater than those in Chadegan area. Grazing intensity in Pishkuh is less than that in Poshtkuh region and there is no significant difference between grazed and protected sites in Pishkuh. But, there is a significant difference between grazed and protected plots in Poshtkuh due to a higher grazing intensity. Higher C_mic/C_oc and lower qCO2 suggest that the quality of organic matter is better in Poshtkuh and Pishkuh. In conclusion, highly degraded rangelands in Pishkuh and Poshtkuh seem to be able to recover very quickly with proper management, while Chadegan region needs a much longer period of time to restore.

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This study used a Ricardian approach to measure the impact of climate change on Iranian wheat production and analyzed potential impacts of further climate changes. The study utilized time series data for the period 1984-2004 pooled over 17 provinces. Results showed that climate change has significant nonlinear impacts on net revenue per hectare of wheat in Iran. The results also showed that rise in temperature and reduction in rainfall by the year 2100 will cause the reduction in land value by 41 %, because of increased greenhouse gas emission.

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Under different climatic conditions of Iran, the evaluation of evapotranspiration (ETo) models sensitivity to meteorological parameters, prior to introducing the superior performance model, seems quite necessary. Using a 35-year (1971-2005) climatological observations in Hamedan, this study compares the sensitivity of different commonly used evapotranspiration models to different meteorological parameters within the IPCC recommended variability range of 10 to 20% during the growing season (April-October). The radiation and temperature-based ETo models include: Penman-Monteith -FAO56 [PMF56], Jensen-Haise [JH1,2], Humid Turc [TH], Arid (semi) arid Turc [TA], Makkink [MK], Hansen [HN], and Hargreaves-Samani [HS]. Results indicate that all the above-mentioned ETo models show the highest sensitivity to radiation and temperature parameters. This implies that special care is required when we apply model-generated radiation and albedo parameters in such ETo models. It is predicted that by 2050, as a result of global warming, the cold semi-arid climates of Iran will cause an average evapotranspiration rise of about 8.5% in crop reference during the growing season.

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Climate change has important effects on earth environment and human life. Therefor, investigation and study of climate change is very essential. This study investigated rainfall, temperature, relative humidity and wind variability by analyzing data for annual and monthly climatic factors collected at 13 synoptic stations (industrial cities of Iran) by using Mann-Kendall test. The results of monthly rainfall trends showed that most of synoptic stations have significant positive and negative trends in winter and spring months. About 23% and 1.7% of stations have significant negative and positive trends, respectively, in annual trend of this factor. The results of monthly number of rainy days showed the major number of significant trends occurs in spring. In autumn (September, October and November) like as summer most of the stations have no significant trends. Analyzing the annual number of rainy days trends also showed that 4 stations have significant positive trends and 2 stations negative trends. Trend of greatest daily precipitation is low throughout the year, so there is not any significant trend in winter. Annual investigations confirm the seasonal investigations. The major number of significant trends in monthly mean maximum temperature occurs in summer but there are not any significant trends in winter and March. The trend of mean minimum temperature is approximately high in all of the seasons and the major number of significant trends occurs in summer and autumn and then in spring and ultimately in winter. In annual investigation, most of the stations showed positive trends and only Oroomieh station has negative trends. Trend of mean temperature is high except for winter. Most of the stations showed positive trend, indicating increasing trends in this factor. Annual studies vertify the positive trends and about 63% of stations have significant positive trends.

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Soil temperature is one of the important variables in hydrology, agriculture, meteorology and climatology studies. Owing to the fact that soil temperature is only measured at synoptic stations, reconstruction of this variable in other places is of great importance for many relevant agricultural surveys. Using 10-year (1996-2005) daily meteorological observations, including: air temperature, global solar radiation, precipitation, relative humidity, vapor pressure, wind speed and air pressure data, different empirical relationships are suggested. At statistically significant level (P<0.05), the suggested regressions are reliable for estimating soil temperature in various depths (5, 10, 20, 30, 50 and 100 cm) and different climate types. Using soil temperature as the dependent variable and the other meteorological parameters as the independent variables, the multivariable relationships are classified accordingly. The results indicate that the impact of meteorological parameters on soil temperature is not the same. At statistically significant level (P<0.05), the mean daily air temperature presented the highest correlation coefficients with soil temperature for all climate types (on average, from R2>0.91 for warm semi-arid, to R2>0.85 for humid climates). Other results highlighted that the correlation coefficients decreased as the soil depth increased. The behavior of statistical validation criteria of the suggested relations are also discussed for all the mentioned climates.

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Climate change has different impacts on extreme events such as flood and drought. However, in Iran there are few researches about the impacts. This research was aimed to investigate maximum annual discharge (magnitude and frequency) that may occur due to climate change in Aidoghmoush Basin during 2040-2069 (2050s). At first, monthly temperature and precipitation data of HadCM3 model under the SRES emission scenario, namely A2 , was provided for the basin. Then, these data were downscaled spatially and temporally to Aidoghmoush basin by proportional and change factor downscaling methods. Results showed that the temperature increases (between 1.5 to 4) and the precipitation varies (30 to 40 percent) in 2040-2069 compared with baseline period (1971-2000). A semi-conceptual model (IHACRES) for simulation of daily runoff was calibrated. Downscaled temperature and Precipitation for 2050s were introduced to IHACRES and daily runoff was simulated for the future. Probability distribution was fitted to maximum annual discharge series and the maximum discharge regime of the future was compared with the baseline. Results indicated that climate change affects Maximum discharge in the regime of the basin. Also, the analysis showed that the intensity of maximum discharges for the time period less than 50 does not show any significant difference but by increasing the return period, the intensity increases in future periods. Moreover, it was shown that the probability of maximum discharges with constant intensity will decrease in the future compared to the baseline.

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Rainfall erosivity force as on important factor in soil erosion and sediment yield has been introduced in different indexes. The objective of this study was to determine suitable rainfall erosivity indices for two climates of semi-arid in Maravetape and very humid in Sangdeh, both in Khazar watershed, by correlation between rainfall erosivity indices and sediment outflow from erosion plots. For this purpose, the rainfall intensities in different time steps and the amount of rainfalls of 12 events in Maravetape and 11 events in Sangdeh have been used. Twonty five rainfall erosivity indexes were calculated based on rainfall intensity. The amount of soil loss measured after each rainfall event in 1.8×22.1 m2 erosion plots. The results of the study revealed that in very humid climate of Sangdeh and in semi-arid climate of Maravetape had high correlation of 0.803 and 0.727 (at the level of 99 percent) with sediment yield and they were applied indices in these climates of Khazar watershed. In general, the groups of 10 and 30 minutes are better than other erosivity indices in the study areas.

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Soil characteristics are affected by climate. Available potassium is one of the most important soil fertility indices. This study was conducted to determine the availability of potassium using Quantity- Intensity (Q/I) relationships in Vertisols of Isfahan and Chaharmahal-Va-Bakhtiari provinces with aridic and xeric moisture regimes, respectively. Soil mineralogy showed that smectite was the dominant clay in Chaharmahal-Va-Bakhtiari soil. The results showed that the activity ratio of K (AReK) in the soil solution of the surface soil in Isfahan and Chaharmahal -Va -Bakhtiari soils, ranged from 0.019 to 0.11 and 0.0037 to 0.0078 mmol.L-1 respectively. The labile K (∆K0) in Isfahan and Chaharmahal Va Bakhtiari soils ranged from 0.23 to 3.8 and 0.72 to 1.6 mmolkg-1, respectively. Potassium on specific sites (KX) in Isfahan and Chaharmahal-Va-Bakhtiari soils ranged from 2.8 to 7.1 and 2.6 to 3.7 mmolkg-1 respectively. The potential buffering capacity (PBCK) in Isfahan and Chaharmahal-Va-Bakhtiari soils ranged from 12 to 36 and 191 to 201 mmolkg-1/(mmolL-1)0.5 respectively. The results suggested that the Q/I parameters were affected by soil depth. In all of the soils studied, PBCK increased with soil depth.

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Paleosols provide invaluable data on paleoclimatic conditions of the area. These soils widely exist in central Iran. Micromorphology and clay mineralogy are among valuable techniques which are useful for interpretation and identification of these soils. The present research was performed to compare the micromorphology and clay mineralogy of paleosols and modern soils of Jiroft area. After field studies, 4 pedons (located on different geomorphic surfaces including stable mantled pediment, stable and unstable transitional surfaces of pediment and alluvial plain, and stable surface of alluvial plain) were sampled for physicochemical, micromorphological, and clay mineralogical analyses. Clay coatings in argillic horizons of paleosols were found during micromorphology observations. On the other hand, clay coatings in present soils were only found in natric horizons, which were attributed to high amounts of Na in these soils. Moreover, smectite, palygorskite, illite, chlorite, and kaolinite clay minerals were recognized in paleosols, but chlorite was not detected in modern soils. The presence of palygorskite in the soils under study was related to the stability of geomorphic surface. Results of the present research showed that a more humid climate was present at the time of paleosols formation.

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This study performs trend analysis of hydroclimatic varibles and their possible effects on the water resources variability. Nonparametric Mann-Kendall and spearman tests were used to investigate trend analysis of mean annual and 24-hr maximum rainfall, flood and low flow parameters of 23 hydrometery and 18 synoptic stations in Sefid-Roud basin. The results showed that mean annual and 24-hr rainfall parameters are decreasing in few stations while most of stations representing negative trend for low flow and flood time series. Applying Sequential Mann-Kendall test revelad that this negative trend is started from 1965 to 1970 for rainfall parameters and from 1970 to1980 for flow (low flow and flood) parameters. Results show that climate change has probability affected variability of climatic variables, while changing of land use may have aslo affeteced extreme flow trends during recent decads. Therefor it can be noted that combination of climate chanege effects and human activities on water recources have affected the negative trend of hydroclimatics variables.

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Due to the important role of climatic parameters such as radiation, temperature, precipitation and evaporation rate in water resources management, this study employed time series modeling to forecast climatic parameters. After normality test of the parameters, nonparametric Mann-Kendall test was used in order to do trend analysis of data at P-value<0.05. Relative humidity and evaporation (with significant trend, -0.348 and -0.42 cm, respectively), as well as air temperature, wind speed, and sunshine were selected for time series modeling. Considering the Autocorrelation function (ACF) and Partial Autocorrelation function (PACF) and trend of data, appropriate models were fitted. The significance of the parameters of the selected models was examined by SE and t statistics, and both stationarity and invertibility conditions of Autoregressive (AR) and Moving average (MA) were also tested. Then, model calibration was carried out using Kolmogorov-Smirnov, Anderson- Darling and Rayan-Joiner. The selected ARIMA models are ARIMA(0,0,11)*(0,0,1), ARIMA(2,0,4)*(1,1,0), ARIMA(4,0,0)*(0,1,1), ARIMA (1,0,1)*(0,1,1), ARIMA (1,0,0)*(0,1,1) for relative humidity, evaporation, air temperature, wind speed and sunshine, respectively. The fitted models were then used to forecast the parameters. Finally, trend analysis of forecasted data was done in order to investigate the climate change. This study emphasizes efficiency of time series modeling in water resources studies in order to forecast climatic parameters.

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Quantitative evaluation of evapotranspiration on a regional scale is necessary for water resources management, crop production and environmental assessments in irrigated lands. In this study, in order to estimate ETo and because of few synoptic stations and also little recorded meteorological data in North Khorasan Province, Iran, with arid and semi-arid climate, 7 stations from neighboring provinces were used. Reference evapotranspiration was calculated using 6 different methods which required a small amount of input data, including Class A pan, Hargreaves-Samani, Priestly-Tailor, Turc, Makkink and the method proposed by Allen et al (1998) to estimate ETo with missing climate data. Besides, the standard FAO-Penman-Monteith was used (because there was no Lysimetric data in the region) to evaluate the applied formulas. Since there was no agreement over the appropriate method to calculate ETo in the selected stations, by using significance test of regression lines, a linear regression equation was computed for each month, in order to convert the best calculating method to FAO-Penman-Monteith formula. Evaluations of these equations showed their acceptable accuracy, in comparison with the previous researches, specifically for cold months (MAE values ranged from 0.3 to 1.4 mm/day).

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During the past few decades, the southern part of the Caspian Sea has more frequently experienced extreme climatic events such as drought and flood. Trend analysis of hydro-climatic variables was conducted using non-parametric Mann-Kendall test and regression test for Neka basin in the north of Iran.       Trends of precipitation and stream flow characteristics including maximum flow, mean flow and low flow indices were analyzed at the annual, seasonal and monthly time scales from 1358 to 1391 (34 years). Results showed a general decrease in annual and winter precipitation and decrease in daily maximum precipitation, with an increased trend in daily maximum precipitation of spring season. A decreasing trend was observed in 7-day low flow in summer for all sub-basins. Annual and monthly mean flows specifically in winter in all sub-basins decreased, but annual maximum flow increased from upstream to downstream. Land use changes showed that deforestation and urbanization increased during 34 years in the mid and downstream sub-basins. The analysis showed that low flow indices and mean flows are strictly sensitive to climate change. Overall, from hydrological perspective, these results indicate that the study region is getting dryer and facing more severe drought events. The results of this study can predict future droughts to make better decisions for irrigation planning and management of water resources.

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This study investigated the effects of climate change on the evapotranspiration amount and water balance in the Zayandeh-Rud river basin. Two important weather stations; Isfahan and Chelgerd stations, located in the East and West of the basin respectively, were selected for investigation in this study. The combination of 15 GCM models were created based on the weighting method and three patterns of climate change including the ideal, medium and critical were defined. Using the proposed patterns, the effects of climate change on temperature and evapotranspiration in Isfahan station and precipitation in Chelgerd station were estimated under the A2 and B1 emissions scenarios. Two indices were considered to determine the sustainability of agricultural water consumption in the study area. Ratio of evapotranspiration in the East part of the basin to precipitation in the West part was defined as EPR index (Evapotranspiration-Precipitation Ratio), and the ratio of maximum agricultural water deficit to the amount of agriculture water need, was considered as maximum deficit index (MD). Results showed that the annual temperature would increase between 0.63-1.13°C in the eastern part of the basin. The west precipitation in the basin would reduce between 6.5-30% in the ideal to critical patterns. Summer season, showed the most amount of increase in the temperature, and winter season, showed the most amount of decrease in precipitation. The A2 emission scenario showed more temperature increase and more precipitation decrease in comparison with the B1 emission scenario and also indicated that the potential evapotranspiration would increase by 3.1 to 4.8% in the basin. The EPR index will increase between 13-52% and MD index will increase between 9-35% in Zayandeh-Rud river basin under different climate change patterns. The results revealed the imbalance between agricultural water use in eastern part and the precipitation in the western part of the basin. In other words, in these conditions, appropriate management strategies and planning should be implemented to ensure the sustainability of water resources in Zayandeh-Rud River Basin.

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With regard to the confirmation of climate change in most regions of the world and its effects on different parts of the water cycle, knowledge of the status of water resources is necessary for proper management of resources and planning for the future. Hence many studies have been done in different areas with the aim of analyzing the impact of climate change on hydrological processes in the upcoming periods. In present research, the effect of climate change on surface runoff in Bazoft watershed has been studied. Bazoft watershed, located in North-West of Chahar Mahal & Bakhtiari province, has significant contribution in the production of water resources of the region due to its special topographical and geographical status. In this study, climatic model – HadCM3- and A2 and B2 emission scenarios have been used to assess uncertainty in forecasting climate change. For this purpose, a statistical model –SDSM- has been applied to downscale large- scale precipitation and temperature data and hydrological model –WetSpa- has been used to simulate runoff. After calibration of the hydrological model, downscaled precipitation and temperature data in near future (2020-2050) and far future (2070-2100) periods were introduced to WetSpa model and runoff was simulated for mentioned periods. Results of this study represent suitable performance of SDSM model in downscaling climatic data, especially minimum and maximum temperature. Also, performance evaluation of Wetspa model shows proper performance of this model for runoff simulation in Bazoft watershed, so that Nash- Sutcliffe efficiency during calibration and validation was 0.63 and 0.65, respectively. Moreover, assessing the amount of predicted runoff for future periods indicates an increase in annual runoff in the Bazoft watershed under both A2 and B2 scenarios.

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This study aims to investigate the changes of minimum and maximum temperature variables under the impact of climate change for time period of 2015-2100 in the Zayandeh-Rud River Basin. The outputs of 14 Global Climate Models (GCMs) under three green-house emission scenarios (RCP2.6, RCP4.5, and RCP8.5) are employed from the Fifth Assessment Report (CMIP5) of Intergovernmental Panel on Climate Change (IPCC). A novel statistical downscaling method using a Bayesian Relevance Vector Machine (RVM) is used to project the impact of climate change on the temperature variables at regional scale. The results of the weighting average of the GCMs show that the various models have different accuracy in the projecting the minimum and maximum temperatures in the study area. The results demonstrate that the MIROC5 and CCSM4 are the most reliable models in projecting the maximum and minimum temperatures, respectively. The highest increase for both maximum and minimum temperatures was obtained in winter.
    On the annual basis, the maximum temperature will increase by 0.18-0.76 °C and 0.25-1.67 °C, respectively, in the near and long-term future periods under different emission scenarios. The annual minimum temperature will increase by 0.28 to 0.82 °C and 0.24-1.56 °C, respectively, in the near and long-term future periods. In a general view, changes in maximum temperature will be slightly higher than minimum temperature changes in the future.
 

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