مجله مدیریت بیابان
پیاپی 23 (پاییز 1401)

Long-term drought prediction is of considerable importance in water resources management. Time series models are appropriate tools to predict climatic events. In this study, the Reconnaissance Drought Index (RDI), which is based on precipitation and potential evapotranspiration, was applied to calculate droughts of Yazd synoptic station at time scales of one, three, and six months from 1961 to 2018. The period 2006-2018 was selected as the forecast period. Drought data of the forecast period were not considered to the applied models. Results showed that the pattern of drought data at 1, 3 and 6-month time scales in the Yazd synoptic station is seasonal. The SARIMA is a univariate time series model created by adding a seasonal component to the ARIMA model. The SARIMAX multivariate model is created by adding parameter covariate variable (exogenous variable) to SARIMA. In the present study, the efficiency of the seasonal univariate model (SARIMA) and seasonal multivariate model (SARIMAX) in predicting drought in arid regions were compared. To implement the SARIMAX model to predict droughts, precipitation and potential evapotranspiration were provided to the model as covariates, separately. The results of the coefficient of determination (R2) between observed RDI and predicted RDI values by SARIMA showed that the model offers higher performance on 3 and 6-month time scales with 0.66 and 0.71, respectively. The results of the SARIMAX model showed that in one-month time scale, the SARIMAX model based on potential evapotranspiration with 0.60, and for 3-month time scale, the SARIMAX model based on precipitation with 0.79 performed better. In 6-month time scale, the performance of the model for the both covariates were almost the same with the coefficient of determination of 0.79. Comparison of the results of the two models showed that the performance of the SARIMAX model is higher than the SARIMA model for drought predicting in arid regions.

The preparation of geological maps based on field data and the application of aerial photographs have always been an error because of the structural diversity of the earth and the difficulty of accessing certain regions. But in recent decades, the use of satellite imagery has but in recent decades, the use of satellite imagery has gone a long way to increasing the accuracy and timeliness of geological mapping. The purpose of the current study is to investigate the applicability of Landsat 8 satellite images and object-oriented pixel classification methods in mapping the geological formations of some part of the Shirkuh Mountain range in Yazd province. This area is part of the scattered mountain range of Central Iran with a dry climate and minimal vegetation. Initially, enhanced operations were performed to identify geological information’s using MNF, PCA and FCC processing. Then, the images were classified using object-oriented algorithms (BAYES, SVM, KNN, Decision Tree and Random Forest), neural network (ARTMAP, RBF, MLP and SOM), and base pixels (Maximum Likelihood, Minimum Distance, Mahalanobis and SAM). Next, the error rate of each method was calculated using Boolean logic and kappa coefficient. The results showed that the maximum probability classification with kappa coefficient of 75% in the base pixel category, Fuzzy ARTMAP classification in neural network method with kappa coefficient of 72% and Bayesian classification in object-oriented method with kappa coefficient of 82% have the best results among other methods. These results show that the methods mentioned in the identification and separation of geological formations are effective. The SAM of pixel-based methods, SOM of neural network methods and RF of object-oriented methods with 49%, 64% and 61%, respectively, showed the lowest accuracy in each category.

Lack of rainfall and its high temporal and spatial variation are the main problems of vegetation restoration in Iran.  Rainfall harvesting methods can play an effective role in improving soil moisture. Rainfall harvesting operations have a great impact on the structure and function of ecosystems. Therefore, the present study investigates the changes of soil properties as a result of implementing two rainfall harvesting methods (water spreading system and micro-catchment) in arid rangelands of Hormozgan province. First, 45 soil samples were taken from control, micro-catchment and water spreading system sites and their physical and chemical properties were measured in the soil laboratory. One-way analysis of variance was used to compare the different sites in terms of soil properties. The rate of change index was used in order to assess the performance of soil properties and the overall performance of each of the rainfall harvesting methods compared to the control. Synergy and trade-off relations between soil properties were investigated using Pearson correlation coefficient. The results showed that except EC, pH, TNV, water spreading system had a significant effect on soil properties. EC, pH, TNV, calcium, magnesium, nitrogen and sand had negative performance in the water spreading system, and the rest of the soil properties had positive performance. The overall performance of soil properties was 31 and 11% in the micro-catchment, and 52 and 25% in the water spreading system. Sand had a significant trade-off relationship with most soil chemical properties. The highest trade-off was observed between sand and silt (p <0.01, R2 = -0.99). The highest synergy was observed between silt and phosphorus (p <0.01, R2 =+0.87), and next phosphorus and OC (p <0.01, R2= +0.72). In general, the positive impact of water spreading system on the soil properties of arid rangelands was greater than the micro-catchment in this region.

Data on the different types of crops and cultivated areas were extracted from 11 cities of South Khorasan province in the growing season of 2019-2020 to evaluate the biodiversity of agricultural crops in this province. Subsequently, this information was divided into various groups to calculate biodiversity indices. Crop categorization was based on the consumption type (cereals, beans, industrial crops, vegetables, grapevine, forage crops, and medicinal plants) and plant family. The finding indicate that 35 crop species are grown in this province. The largest area cultivated is cereals at 65.01%, the second for forage crops at 11.1%, and the third of medicinal plants at 10.8%. According to the results, the production systems of the agricultural ecosystems of South Khorasan do not show a rich diversity. The diversity index was very low among all agricultural groups and plant families. Of the groups studied, cereals, medicinal plants and fodder crops were more diversified than others. The groups of plants with the greatest variety were Poaceae and Iridaceae. Qaen and Boshruyeh cities had a more desirable diversity than the other cities resulting in the richness of the species and a higher homogeneity and Shannon index. However, the diversity indices were low in cities of Ferdows, Sarbisheh, Darmian, and Khoosf. Since the preservation and development of biodiversity is one of the key components to achieve stability in agriculture, attention to the biodiversity of agricultural crops seems to be crucial in South Khorasan province, especially in low-diversity cities.

Due to the water shotages in arid and semi-arid climates, rainfed agriculture faces severe challenges. It is therefore essential to carry out specific studies on the efficiency factors of rain-fed crop growth. The purpose of this study was to assess the factors affecting the duration of the different phenological stages of rain-fed barley in a semi-arid region. For this purpose, duration of phenological stages for five different growth periods of rain-fed barley including sowing-emerge, emerge-tillering, tillering-stem, stem-flowering, and flowering-maturity were extracted at the Sararoud station, Kermanshah, during the period of 2000-2015.  By calculating 12 variables for these periods, the variables with significant impacts were detected for each of them and Principal Component Analysis (PCA) technique was used to assess the impact of these variables on different phenological stages duration. The results showed that between different selected variables, the degree-days-based variables (GDD and PTU) and absorb radiation-based (net radiation and daily mean soil surface temperature) showed the highest impact on all of the phenological stages duration. Each of the evapotranspiration-based variables, soil moisture supply variables and complementary variables influenced duration of two growth stages. The highest variability of the different growth periods which explained by the selected variables in the current research using principal component analysis was obtained for sowing-emerge stage. The overall results showed that the principal component analysis not only has a high capability to detecting effective factors on the different phenological stages duration, but also is a powerful tool to regulate the interrelate impacts between variables..

The loss of water from reservoirs in the country, especially in the central and southeast regions, due to the dry climate and high temperatures are significant, causing stress on water resources. There is a need to reduce the amount of evaporation from the surface of the reservoirs in order to conserve the country's usable water resources of the. In the present study, the effectiveness of Palma dactylifera L. mats with two coverage levels of 50 and 100% as evaporation reducion coatings- has been studied. To examine the performance of the mentioned methods on reducing water losses, Colorado evaporation pans were used at the Semnan University. The effectiveness of the mentioned coatings was studied with three replicates and in comparison, with the control for 30 days in different seasons of 2018, using the comparison means method. Based on the results of average comparison test using Duncan's method, the 50% and 100% coatings showed a significant 1% difference with the control in terms of evaporation and water temperature. Results indicate in spring, pans covered with 50% and 100% mats reduced evaporation by 9% and 70%, respectively, and by 0 and 72%. in summer. In autumn, it showed a decrease in evaporation of 39% and 72%, and in winter, and a decrease in evaporation of 38% and 78% compared to the control. In general, palm mat Palma dactylifera L. with 100% coverage has shown the best performance on the surfaces of Colorado evaporation pans. Results show that in arid lands and desert regions, palm mat covering are expected to reduce evaporation from water reservoirs and basins.