JWSS - Journal of Water and Soil Science

Drought as a natural hazard is a gradual phenomenon, slowly affecting an area; it may last for many years and can have devastating effects on the natural environment and in human lives. Although drought forecasting plays an important role in the planning and management of water resource systems, the random nature of contributing factors contributing to the occurrence of and severity of droughts causes some difficulties in determination of the time when a drought begins or ends. The present research was planned to evaluate the capability of linear stochastic models, known as multiplicative Seasonal Autoregressive Integrated Moving Average (SARIMA) model, in the quantitative forecasting of drought in Isfahan province based on the Standardized Precipitation Index (SPI). To this end, the best SARIMA models were chosen for modelling the monthly rainfall data from 1990 to 2017 for every 10 synoptic stations in Isfahan province to forecast their monthly rainfall up to five years. The monthly time scale SPI values based on these predictions were used to assess the drought severity of different stations for the 2018- 2022 time period. The station results indicated a weak drought at the 2019- 2022 period for Isfahan, Kashan and Naeen, a severe drought in 2019 for Ardestan and Golpaygan, and a weak one in 2019 for the East of Isfahan, KabootarAbad and Shahreza stations. All other stations, except Golpayegan, Isfahan, Kashan and Naeen, faced a severe drought in 2018.

The purpose of this study was to investigate the relationship between time and spatial features of meteorological, hydrological and agricultural droughts in Karoon 1 Dam basin. Meteorological and statistical data were accordingly selected to evaluate the drought situation between 1993 and 2016. The results showed that hydrological droughts occurred in the meteorological drought and had a very high correlation with this year's meteorological drought. The most severe droughts occurred between 2006 and 2011. Studies also showed that every three years, the basin was accompanied by a meteorological drought and then a hydrological drought. The results also showed that the highest correlation was observed with the 12-month meteorological index, with a delay of 3 months, and the 6-month meteorological and hydrological index with a delay of 3 months and a three-month hydrological drought index with a delay of two months. Therefore, it could be concluded that hydrological droughts showed a delay of almost two to three months in the entire catchment area; since this period was 4 months or more, the correlation between these two indicators was eliminated and decreased. Also, due to drought zones, during the period from 1993 to 2009, most of the droughts were caused by rainfall reduction in the southwest of the province, and this was associated with a reduction in runoff in its hydrometric stations. Of course, in 2009-2012, the runoff status had been temporarily improved, and from 2012 to 2017, the drought situation had again returned spatially to the previous routine.

Drought, as one of the most complicated natural events, causes many direct and indirect damages each year. Hence, single variable identification and monitoring of drought may not be appropriate enough for decision-making and management. In this study, in order to monitor the meteorological-agricultural drought in Chaharmahal and Bakhtiari province, Multivariate Standardized Drought Index (MSDI) was calculated using precipitation and soil moisture variables. In addition, to evaluate the performance of MSDI in drought identification and monitoring, Standardized Precipitation Index (SPI) and Standardized Soil Moisture Index (SSI) were used for meteorological and agricultural drought monitoring, respectively. MSDI was calculated based on the soil moisture and precipitation joint probabilities. We used the Gringorten probability as an empirical method and Archimedean copulas as the parametric method to calculate the joint probability between soil moisture and precipitation time series. The results indicated that MSDI was twice more capable of detecting drought as SSI and SPI. Furthermore, the MSDI-based drought monitoring results showed Charmahal and Bakhtiari province had experienced severe meteorological-agricultural drought in 2000, 2008, 2011 and 2014.

Long-term drought effect is one of the main factors of global climate change, with  consequences for soil biogeochemical cycling of carbon and nitrogen and the  function of soil ecosystem under drought conditions. We hypothesized that 1) the Bromus inermis, Dactylis glomerata and festuca arundinacea species would differ in their rhizosphere responses to drought and 2) combined plant species and drought would have offsetting effects on the  soil biological traits. We tested these hypotheses at the long-term drought field expreiment at the  Lavark Farm of Isfahan University of Technology by analyzing soil microbial biomass carbon and nitrogen and activity of β-glucosaminidase in the rhizosphere of Bromus inermis, Dactylis glomerata and festuca arundinacea species. Soil microbial biomass carbon and nitrogen responses to drought depended on plant species,  such that the highest MBC was recorded in the Bromus inermis rhizosphere, while the  lowest was in the Dactylis glomerata rhizosphere, thereby suggesting the greater microbial sensitivity to drought in the Dactylis glomerata rhizosphere. Genotype variations (drought tolerate and sensitive) mostly affected the change in the β-glucosaminidase activity, but they were not significantly affected by drought treatment and plant species. In general, the positive effects of  the plant genotype could offset the negative consequences of drought for soil microbial biomass and traits.

Several indices are used for drought identification and quantification. In this paper, the new Standardized Palmer Drought index (SPDI) was introduced and then the drought condition of Chaharmahal-Va-Bakhtiari Province was studied using this index. For this study, 11 synoptic, climatology, and evaporation meteorology stations were selected. Essential information in this investigation includes monthly temperature, monthly precipitation, and soil moisture measurement. To estimate SPDI, moisture departure, was first calculated on a monthly time scale. Then, converted to cumulative moisture departure values in different time scales including 3, 6, 9, 12, and 24 months. The best statistical distribution (GEV) was then fitted to cumulative departure. These values were then standardized to have the SPDI. The results showed that, as soil moisture affects SPDI estimation, it will be more valid for analyzing and monitoring drought conditions, especially for agricultural drought. Also, the results showed that 2000, 2001, and 2008 years were the driest time in this Province from 1988 to 2012. Moreover, drought frequency was found out in the western half of the Province more than in the other parts.

The upcoming climate change has become a serious concern for the human society. These changes, caused and aggravated by the industrial activities of the international community and the increase in the concentration of greenhouse gases in the atmosphere, are seen as a threat to the food security and environment. Temperature change and precipitation are studied in the form of different probabilistic scenarios in order to have an outlook for the future. The present study was conducted to address the effects of climate changes on temperature and precipitation in Qazvin plain in the form of five AOGCMs including Hadcm3, CSIRO-MK3, GFDL, CGCM3 and MICROC3.2, and 3 greenhouse gas emission scenarios of A1B, A2 and B1, based on different possible scenario combinations in the next 30 years, 2021-2050 and 2051-2080 (near and far future). On basis of the study results, all 4 target stations, on average, will have experienced a change between two ratios of 0.5 and 1.4 of  the observed precipitation period  by the end of 2050, and the mean temperature will have had a change  between -0.1 to 1.6 °C, relative to the observed period.  By the end of 2080,  the  precipitation will also have fluctuated between the two proportions of 0.5 and 1.7 times of the observed precipitation period and the mean temperature will touch an increase between 0.6 and 2.6 °C. Both SPI and SPEI indices suggest the increment in the number of dry periods in the near and far future. However, the total number of negative sequences differed considering the 3, 12 and 24-month intervals at the stations level. Given the SPEI index, as compared to the base period, the total negative sequences of drought and number of dry periods will increase at 3 stations of Avaj, Bagh-Kowsar and Shahid-rajaei-powerhouse and decrease at Qazvin station in the future; however, SPI gives different results, such that  for Bagh-Kowsar, there will be an increase in both total negative sequences of drought and number of dry periods, as  compared to the baseline period; three other stations will have more dry periods, specifically, but less total negative sequences. The results reported that the drought events would become severe, and the wet events would become extreme in the future.

At present, the occurrence of dust storms is one of the most important environmental problems in Khuzestan Province, and the south and southeast regions of Ahwaz have been recognized as one of the interior dust sources and are the priority of corrective operations. Given that land use change is one of the desertification factors in the mentioned region, therefore, modeling its changes is necessary and provides useful information for planners to control and revive the degraded lands. The objective of this study was to evaluate the efficiency of the CA-Markov model in predicting land use changes in the dust source of south and southeast of Ahwaz based on two long-term and short-term approaches. In the long-term approach, land use maps of 1986 and 2002 years and in the short-term approach, land use maps of 2002 and 2007 years have been used to predict land use for the year 2016 and then the simulation results were validated. The results showed that the values ​​of allocation error, quantity error, and kappa coefficient for the long-term approach were 42.55%, 13.95%, and 0.08 respectively, and for the short-term approach were 12.56%, 10.42%, and 0.22 respectively, which indicates the weak ability of the CA-Markov model to evaluate the desertification trend in the dust Source of south and southeast Ahwaz. Use of uniform transition rule throughout the simulation period without considering the factors and processes affecting land use change, the non-same trend of land use change during study periods, changes due to human activities, drought, and long forecast period can be the reasons for the poor performance of the CA-Markov model to predict the desertification trend the dust Source of south and southeast Ahwaz.

Drought is one of the most complex natural disasters due to its slow onset and long-term impact. Today, the use of remote sensing techniques and satellite imagery has been considered a useful tool for monitoring agricultural drought. The objective of the present study was to evaluate spatial and temporal monitoring of agricultural drought in the lake Urmia catchment area with the ETDI drought index which is calculated from Nova satellite images based on actual evapotranspiration from the SEBS algorithm and compared with the ground index SPI. For this purpose, 248 AVHRR sensor images and NOAA satellites during the statistical period of 1998-2000 and 17 meteorological stations with a statistical period of 30 years were used to calculate the indicators. To determine agricultural lands, six thousand points were marked for different uses and their actual evapotranspiration was calculated using the SEBS algorithm. The results showed that with the onset of the drought period in 1998, the ETDI index indicated 9.4% in weak drought conditions in May and 90.6% in normal conditions. Over time, in June of 1998, the situation was different with 95% in a weak drought situation and 5% in a normal situation for the city of Tabriz. In July, the entire catchment area experiences a slight drought. Then, in August, 84% of the basin is in normal condition and 16% in Tabriz and Urmia are declared weak drought. It was also founded that the ETDI drought index due to the combination of visible and infrared bands and its combination with terrestrial data has a physical meaning and has high certainty and predicts drought faster and more accurately.

Salinity and water scarcity are limiting factors for sustainable agricultural production. The cultivation of resistant plants to environmental stresses is one of the important management factors for sustainable production. The objective of this study was to determine the water requirement and plant response coefficients to water deficit stress (K_y) in different growth stages under the Khuzestan province climate. This study was performed on the quinoa cultivar Titicaca in Ahvaz City in 2019 in a randomized complete block design with 13 treatments and three replications. Treatments include full irrigation and application of three levels of water deficit stress (30, 50, and 70% of allowable soil moisture depletion) at four different stages of plant growth. The duration of the initial, developmental, middle, and late growth stages of quinoa was 24, 28, 32, and 18 days, respectively (total growth period=102 days). The highest quinoa yield was obtained in full irrigation treatment (3700 kg ha^-1) with a water requirement of 312 mm. Plant response coefficient to water deficit stress in the initial, developmental, middle, and late stages were 0.8, 0.65, 0.74, and 0.47, respectively. Although quinoa is a drought-resistance plant, it should be noted that the water stress in the two initial and middle stages (quinoa sensitive growth stages to water stress) reduces the quinoa yield significantly that should be considered in the planning of deficit irrigation.

Due to the climatic conditions of Iran, increasing water scarcity, and the effect of drought stress on the efficiency of irrigation water consumption and chemical fertilizers application, an experiment was conducted to investigate the effect of irrigation intervals (6, 9, and 12-day intervals), different levels of nitrogen fertilizer (200, 300, and 400 kg urea per hectare) and cultivation methods (on-ridge or heeling up and in-furrow) on yield and productivity of sugarcane as a factorial design based on randomized complete block design in 3 replications at Hakim Farabi Agro-Industry Company in Khuzestan province. The results showed that the maximum (106.73 tons/ha) and minimum (59.10 tons/ha) sugarcane yields were observed in 9-day and 12-day irrigation intervals, respectively. Also, the highest sugarcane yield (99.89 tons per hectare) was obtained in the treatment of 400 kg urea per hectare and the in-furrow planting method resulted in a higher yield compared to the on-ridge planting method. The highest water productivity in sugarcane stem yield and sugar production with 3.55 and 0.34 kg per cubic meter of applied water, respectively, was obtained in a 9-day irrigation interval. A significant increase in water use efficiency in sugarcane stem yield was observed in 400 kg urea/ha compared to the other two fertilizer levels. However, there was no significant difference in water productivity of sugar yield between different fertilizer treatments. The results showed that 6 and 9-day irrigation intervals in most of the studied traits were not significantly different. Therefore, using a 9-day irrigation interval is suggested in the studied area when the sugarcane cultivation area is high and the amount of available water is limited. In-furrow planting method can also be effective in reducing water consumption. Therefore, deficit irrigation and proper nitrogen fertilizer consumption can be very effective in sugarcane cultivation.