نشریه پژوهش های آبخیزداری
پیاپی 129 (زمستان 1399)

Underground dam is an important hydraulic structure in management water in the arid and semi-arid areas. The aim of this research was to identify appropriate sites for constructing underground dams, where they do not limit construction of other such dams in this region. By benefiting from the Boolean logic, and using the physiographic, topographic, geological, land-use, fault, and aqueduct criteria, the regions that had no limitations for the constructing underground dams were selected. Using the analytical hierarchy process as well as the quantity and quality criteria of water, economic and social, dam reservoir, capacity and land-use, suitable sites for project construction underground dams were prioritized. The inconsistency rate in this research was 0.05. Investigation of the inconsistency rate indicated that the scoring performed for the criteria and sub-criteria studied here were acceptable. The results of prioritization of the region indicated that the watershed slope was the most important criterion in determining suitable site for such projects, thus constructing dams at steep slopes was not economical. Furthermore, given the geological conditions of the region and high score of this criterion in constructing underground dams, this criterion should be paid more attention to in such constructions. Overall, the results indicated that the regions located in the western and central parts of the watershed had a higher score for underground dam construction. Considering the importance of underground dam in dry and semidry regions, it can be stated that by constructing such dams in these regions, it is possible to improve the management of water resources.

Surface soil moisture retrieval using microwave remote sensing, as the most promising method, has been highly valued due to its great accuracy and temporal resolution in broad scales. However, its coarse resolution limits regional scale applications. This study aims to apply the optional downscaling algorithm to generate high resolution soil moisture (θf) over Firoozabad Watershed, Ardabil, Iran. The algorithm integrates the advantage of Sentinel-1 (S-1) radar and the SMAP Radiometer soil moisture to make a linear correlation between the satellite soil moisture (θc) and the radar backscatter (σo) at each coarse pixel. The outputs were compared with the soil moisture measurements collected from individual points in the study area. The values of 0.043 cm3/cm3 and 0.039 cm3/cm3, respectively, were obtained for RMSE and UnbRMSE at 1 km resolution. This result are close to the SMAP’s downscaled target accuracy (RMSE = 0.05, cm3 / cm3). Taken together, point measurement has limitations in terms of spatial representation and spatial extent, especially in a watershed scale data analysis; therefore, utilizing the freely available SMAP soil moisture data and its downscaled version with the S-1 SAR data could be considered as an efficient and low cost tool to be used in research and implementation for the local and regional applications.

Landslides are natural and incidentally man-made phenomena. Developing landslide risk reduction plans in order to preserve the natural and human resources are pivotal. This study sets out to prioritize landslide-controlling factors by using the Shannon’s entropy model and the GIS techniques. A total of 90 landslides were identified using extensive filed surveys and interpreting the Google Earth images. A Landslide inventory map was prepared in the GIS environment together with eleven controlling factors as inputs, namely precipitation, elevation, slope percentage, slope aspect, lithology, land use/land cover, the normalized difference vegetation index (NDVI), and the distance to streams/faults/roads/villages. The results revealed that the land use/land cover, the distance to streams, and the distance to faults were the top-ranked factors of the highest importance in landslide occurrence, while the distance to villages, and the distance to roads were of the least importance. Further, the model validation results attested to the great performance of the adopted model where the area under the receiver operating characteristic curve (AUROC) was 0.879. Considering that about 32% of the watershed is located in the high and very high sensitive area, it is recommended to avoid land use change in landslide-prone areas to reduce relative risk of landslide.

Floodwater spreading (FS) is an efficient and appropriate method for the optimization of runoff utilization, particularly in arid and semiarid region. Beside the reduction of damage caused by the flooding, this technique is also useful in the artificial recharge of groundwater and rangeland restoration. Effects of floodwater spreading on species composition and functional groups were assessed in the Poshtkooh Rangelands of Sari in the Mazandaran Province. Vegetation sampling was evaluated in the FS area, enclosure and a without floodwater spreading (grazing). Sampling was carried out at representative and homogeneous areas of each treatment by the random-systematic method, thus the canopy cover of each plant species was measured in 90 plots of 1 m2/each. Results showed that there were 53 species in floodwater spreading area and 43 species in the enclosure but only 24 species were present in the control area spreading or grazing. Among the studied plant families. The canopy cover of Brassicaceae, Poaceae and Fabaceae was increased by floodwater spreading, shrubs and Chamophytes showed a significant reduction from due to FS as compare with the control area. Comparison of the most functional groups also indicated a reduction in their canopy cover percentage with an increase in floodwater spreading and enclosure. The multivariate analysis showed that the species composition and functional groups of the study area were affected by the FS practices and enclosure; that important and valuable species such as Agropyron elongatum and Onobrychis altissima responded most to such practice. To sum up, our results clearly showed that the FS practices carried out in the area had a positive effect on species composition and functional groups.

Global warming has a serious impact on access to water resources, especially in arid regions due to changes in rainfall and temperature. The Global Circulation Models (GCM) and the Regional Climate Models (RCM) have been considered as the main tools for assessing changes in climatic variables in the future. The difference in the spatial resolution of these models causes the different results in climate change assessment. The performance of the CanESM2 and REMO models was evaluated using statistical criteria in the Jazmourian Watershed. The results indicated that the CanESM2 has performed better than the REMO regional model for predicting climatic parameters. Climate parameter simulation based on the CanESM2 model showed that precipitation will decrease under the RCP scenarios (RCP2., RCP4.5, RCP8.5) by 19.23, 18.55, 14.55 mm, respectively at the Iranshahr Station and 8.31, 10.6, 15.72 mm, respectively at the Bam Station. The mean projected temperature based on the RCP scenarios showed that temperature will increase by 1.57, 2.15 and 3.1 ºC at the Iranshahr Station and 1.84, 2.31 and 3.35 ºC at Bam station under RCP2.6, RCP4.5 and RCP8.5, respectively. Generally, the finding of simulated precipitation and temperature in the Jazmourian Watershed showed that  the long dry periods is more likely to occur in the future as compared to the historical period. Hence, knowing the trend of the changes in climatic variables can help managers and planners to provide required strategies under the future climate change conditions.

Degradation of aggregates due to rain drop impacts leads to surface sealing formation, roughness reduction, filling of soil pores and consequently increase in the runoff rate and soil loss. Despite the effect on aggregate breakdown and formation of surface sealing, rainfall sequence is among the factors that have been less studied so far. Effect of three subsequent rainfalls and surface sealing formation were investigated on runoff and soil loss components in small experimental plots under simulated rainfalls with the intensities of 50 and 90 mm h-1 and duration of 15 min after time to runoff, in two soil types of sandy-loam and sandy-clay-loam, respectively. The results indicated that soil surface seal was formed by subsequent rainfalls in both of the studied soil textures and rainfall intensities. The rainfall sequence had the significant effect (P<0.01) on the time to runoff initiation, runoff volume and runoff termination. Based on the results of a 3D scanning, soil surface roughness decreased from 1.30 to 1.18 in sandy-loam and from 1.80 to 1.31 mm in the sandy-clay-loam soil as a result of rainfall sequence with the intensity of 50 mm h-1. However, soil surface roughness increased and became 2.37 and 1.99 mm in sandy-loam and sandy-clay-loam soils, respectively, at the rainfall intensity of 90 mm h-1. Regarding the effects of vegetation residues on the structural modification and physical protection of surface soil against raindrop impacts, it is suggested to reduce grazing and also to increase the vegetative cover in the area in order to reduce surface sealing.

One of the most important measures for flood management is preparation of a flood susceptibility map. The purpose of this study was to identify susceptible areas to flooding using the maximum entropy model in the Tashan Watershed, Khuzestan Province. A flood inventory map was prepared for the statistical analysis. Of the 169 flooding occurrences, 70% were used for the model calibration and 30% were used for validation. Ten flooding factors, namely: altitude, slope aspect, distance from river, drainage density, slope angle, land use, distance from road, topographic wetness index, plan curvature and lithology were used. The effect and contribution of each environmental parameter was calculated using the response curves and the Jackknife method. Finally, a flooding susceptibility map was prepared in four classes. The receiver operating characteristic curve was used to evaluate the accuracy of modeling. The results indicated that the maximum entropy model had a very good accuracy (AUC=0.885) in identifying the prone areas to flooding, and the land use and distance from road with 50.5% and 20.6% contribution, respectively, had the most impact on the occurrence of flood inundation. Also, about 25% of the watershed area was highly sensitive to flooding. Regarding to very good prediction accuracy of maximum entropy model in detecting susceptible areas to flooding, it is recommended to apply this model for the preparation of the flooding map in other watersheds, especially areas lucking hydrometric stations.

Rainwater harvesting (RWH) in arid and semi-arid regions using micro-catchments (MCS) is an appropriate technique to produce crops and to deal with water shortages. Potential of RWH on the Taleghan Watershed was investigated using MCS covering areas of 100, 25 and 6.25 m2 under three treatments: furrowing, surface compaction and control (no treatment) during the 2016/2017 hydrological year. The experimental design was complete randomized block in factorial manner with three replications. Volume of the collected runoff was measured after each precipitation event in different seasons. The relationship between the amount and coefficient of runoff (R and Cr, respectively) with precipitation and the threshold of precipitation for runoff production (TPR) was determined. Results showed that the spring precipitation produced 62.5 and 65.5% higher R than the winter and autumn rainfall, respectively. Moreover, surface compaction produced 17.3 and 19.8% higher R and Cr than the control, respectively; it also reduced TPR by 7%. However, under furrowing, the R and Cr values decreased by 22 and 20%, respectively; while, TPR increased by 4% more than the control. Furthermore, the values of R and TPR in larger MCS were less than those of the smaller MCS. Overall, the use of MCS for R harvesting and plant cultivation with surface soil compaction (increasing bulk density by 7%) is recommended in regions where their areas is determined by the plant type.

The temporal and spatial variability of rainfall within and between years is a characteristic of Iran's climate. The aim of this study was to investigate the PCI, SPI, RDI and MFI indices and map their spatial variations. These data were obtained from the Meteorological Organization of Iran. The results idicated that the PCI index had an upward trend in 50% of the stations and a downward trend in the remaining stations. The lowest value of the PCI index was observes for the northern regions in 1992 at the Rasht Station (9.22), and the highest value for southeastern regions in 2008 at the Bandar Abbas Station (76.36). The MFI index had a downward trend of 28 stations with the lowest value of the MFI index in 2010 at the Yazd Station (4.42) and the highest value in 2001 at the Yasuj Station (451.65). According to the PCI index, the rainfall pattern at most of Iran's synoptic stations is seasonal and completely seasonal. The results of drought indices indicated that the SPI and RDI indices were higher in the western regions than the other regions. The severest drought based on both indices was observed at the Bushehr Synoptic Station in 2010. The values of these indices were (-3.4) and (-3.3), respectively. The results also indicated that the RDI index revealed a more severe drought conditions. As the RDI index includes air temperature as a direct factor affecting drought, it is recommended to replace the SPI index with this one. The Fornieh Rain Erosion Map maybe of great help to watershed managers and natural resource experts in planning soil conservation, erosion control, and land use schemes.

Aquifers management is of utmost importance used for supplying the water use in different sectors in the arid and semiarid regions. This research aims to evaluate the quality of groundwater resources and to find suitable locations for the construction of underground dams in the Kouhdasht area (west of the Lorestan Province). To evaluate the water quality for drinking and agricultural purposes, the chemical parameters of groundwater resources were placed in the Schaller and Wilcox diagrams. The results indicated that groundwater quality is desirable for various uses. To identify suitable locations for the construction of underground dams, factors namely: slope, lithology, land use, drainage network density, precipitation, temperature, distances from the village, well, fault, and springs were used. After providing the various data layers, the map of each factor is standardized and weighed using the fuzzy logic and the hierarchical analysis process, respectively. Evaluation of various factors influencing the determination of suitable areas for construction of underground dam revealed that three factors namely drainage network, lithology, and topographic slope with a weight of 0.243, 0.206, and 0.153, respectively, had the greatest impact on the selection of optimal locations. By overlaying the weighted maps provided for each layer in the Arc GIS 10, a map showing the suitable sites for construction of underground dams was produced. Based on the results, 20.35, 15.90, 14.92, 26.28, and 22.54 percent age of the area were evaluated as highly inappropriate, inappropriate, moderately, appropriate, and very appropriate for construction of underground dams, respectively. Performing detailed field surveys in the very appropriate areas, six sites were selected for construction of underground dams. These were located on the path of the fourth-order and greater streams.