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As drought occurs in different climates, assessment of drought impacts on parameters such as vegetation cover is of utmost importance. Satellite remote sensing images with various spectral and spatial resolutions represent information about different land covers such as vegetation cover. Hence, the purpose of this study was to investigate the performance of satellite vegetation indices to monitor the agricultural drought on a local scale. In this regard, satellite images including Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) data were used to evaluate vegetation cover and their gradual changes effects on agricultural drought. Fars province in Iran with relatively low precipitation values was selected as the study area. Modified Perpendicular Drought Index (MPDI), MPDI1, Vegetation Condition Index (VCI), Normalized Difference Vegetation Index Anomalies (NDVIA), and Standardized Vegetation Index (SVI), were evaluated to select the remote sensing based index with the best performance in drought monitoring. The performance of such indices were investigated during 13 years (2000–2013) for MODIS and 29 years (1985–2013) for AVHRR. To assess the efficiency of the satellite indices in drought investigation, Standardized Precipitation Index (SPI) data of five selected stations were used for 3, 6, and 9 month periods on August. The results showed that NDVI-based vegetation indices had the highest correlation with SPI in cold climate and long-term timescale (6 and 9 month). The highest correlation values between remote sensing based indices and SPI were acquired, respectively, in 9-month and 6-month time-scales, with the values of 43.5% and 40%. Moreover, VCI showed the highest capability for agricultural drought investigating in different climate regions of the study area. Overall, the results proved that NDVI-based indices can be used for drought monitoring and assessment in a long-term timescale on a local time-scale.

To manage inland water resources, surveying the performance of remote sensing models for estimating the actual evaporation in arid regions is so important. Hence, this study aimed to assess the performance of two energy balance algorithms including surface energy balance algorithm for land (SEBAL) and operational simplified surface energy balance (SSEBop) in freshwater and saline water bodies. Another purpose of the present study was efficiency improvement in hypersaline lakes. In this regard, a practical salinity correction coefficient was used to overcome shortcomings of the selected models over saline Lake. The analysis of yearly lake water budget was used to assess the selected energy balance algorithms’ performance with a novel approach. These algorithms were investigated at Shahid Kazemi Dam Reservoir (as a freshwater body) and Urmia Lake (as a hypersaline water body) in Iran. The results showed that two selected algorithms estimated the evaporation rate at the selected freshwater body with a proper accuracy. The results showed the root mean square error for SEBAL result (RMSESEBAL) as 2.0 mm/day, correlation coefficient for SEBAL result (RSEBAL) as 0.80 mm/day, and RMSESSEBop and RSSEBop as 1.7 and 0.80 mm/day, respectively. However, these models overestimated evaporation over the hypersaline water body (RMSESEBAL = 88.4 mm/month, RSEBAL = 0.90 and RMSESSEBop = 39.9 mm/month, RSSEBop = 0.94). Salinity correction coefficient improved the results as RMSESEBAL = 19.8 mm/month, RSEBAL = 0.90 and RMSESSEBop = 13.4 mm/month, and RSSEBop = 0.94. In general, the algorithm performance was improved using the salinity correction coefficient in the chosen hypersaline water body.

The Gravity Recovery and Climate Experiment (GRACE) twin satellites introduced a new opportunity to monitor changes in groundwater level. However, the performance of the GRACE-derived Liquid Water Equivalent Thickness (GRACE-LWET) in estimating groundwater-level changes at a local scale requires evaluation. Thus, the main aim of this study is to evaluate the performance of the GRACE-derived estimation in monitoring groundwater-level changes in Iran, which is experiencing decreasing trends and subsequent impacts. Another aim is to investigate the time lag between the water levels derived from the GRACE estimation and direct measurements. Four regions in Iran were studied between the years 2002 and 2016. To evaluate the results of GRACE-LWET, groundwater levels in 144 piezometric wells were measured monthly. The changes of the earth’s mass due to surface-water changes were assessed using four datasets of the Global Land Data Assimilation System. Furthermore, the statistical trend of the groundwater-level changes acquired from the GRACE estimations and observational data was investigated using the Mann-Kendall test and Sen’s slope estimator at a significance level of 0.05. The results showed that the best performance of the GRACE estimations was acquired when considering a 2-month time lag. In this case, the average correlation coefficient of the GRACE estimations against the observational data for the entire study region was 0.57. Moreover, the GRACE-LWET showed a significant decreasing trend for the whole study area using both considered tests. Hence, GRACE-derived estimation of groundwater-level changes can be used in regions with insufficient observational well data with an acceptable accuracy.

The performance of gravity recovery and climate experiment (GRACE) and GRACE-Follow On (GRACE-FO) satellites in estimating groundwater level (GWL) changes on a local scale is a challenging issue. Then, this study aims to investigate the performance of GRACE and GRACE-FO in monitoring GWL changes on a local scale compared to observations at groundwater wells and the results of groundwater modeling. The study utilized hundreds of groundwater observational data points and 180 satellite data from 2002 to 2020 in five Iranian provinces. The data from satellites GRACE and GRACE-FO were modified by subtracting hydrological parameters outputs of the global land data assimilation system (GLDAS) from the satellites’ estimations. The significant trends in GWL changes were studied by Sen’s slope and Mann–Kendall, which represented a significant declining trend in GWL in all studied provinces. Applying 1–2 month time lags to the observational data improved the correlation coefficients between satellite estimations and the observations at groundwater wells. The best correlation coefficients between observational GWL changes and GRACE estimations in Fars, Khorasan Razavi, Sistan and Baluchistan, East Azerbaijan, and Golestan provinces were calculated as 0.53, 0.42, 0.4, 0.51, and 0.36. Those values for GRACE-FO were calculated as 0.95, 0.67, 0.72, 0.78, and 0.3, respectively, which proved the better performance of GRACE-FO compared to GRACE. Meanwhile, the GWL changes estimated from GRACE-FO were compared to the results of groundwater modeling, which was performed by using MODFLOW via the GMS10.4 interface in Azarshahr aquifer located at East Azarbaijan revealed a satisfactory agreement.

Evaluation of groundwater resources in dry areas without enough data is a challenging task in many parts of the world, including Tehran–Karaj plain in Iran, which includes Tehran, the capital city of Iran and Karaj, one of Iran’s biggest cities. Water demand due to increasing agricultural and industrial activities caused many problems in the field of water resources management. In this study, the potential of groundwater resources was evaluated using remote sensing, geographic information system (GIS), and analytic hierarchy process (AHP) for the first time. Digital Elevation Model from Shuttle Radar Topography Mission was used to generate a slope map and drainage density map. Three Landsat-8 satellite images were utilized to provide lineament density and land cover/land use maps. Geological and soil type maps were provided from the Geological Survey and Mineral Explorations of Iran (GSI). Tropical Rainfall Measuring Mission data were used to prepare average annual precipitation map. Discharge values from 102 pumping wells in the time period of 2002–2014 were used to evaluate the results. Seven data layers were prepared, and the geodatabase was made in GIS. The layers and their classes were assigned weights using AHP method. Finally, the layers were overlaid based on their weights, and the potential map of groundwater resources was generated. The area was classified into five zones with very high, high, moderate, low, and very low potentials. The zones covered 5.95, 32.90, 22.70, 10.20, and 28.25% of the study area, respectively. The results showed good agreement with the field data obtained from discharge wells.

Erosion potential method (EPM) and Modified Pacific Southwest Interagency Committee (MPSIAC) are two empirical models for estimating soil erosion and sediment delivery. These models use a relatively simple formulation, but they are still applied in various areas with different environmental conditions. However, evaluation of their efficiency is challenging. Accordingly, the main purpose of this study is investigating the performance of EPM and MPSIAC in estimating soil erosion and sediment yield using sediment rating curve (SRC) methods. Talar watershed in Iran was selected as the study area and suspended sediment load (SSL) of two Shirgah–Talar and Valikbon stations were used to assess the output of the models. Remote sensing and geographic information system were utilized in implementing the models. The estimated sediment yield values by the models were evaluated using the results of least square error regression and quantile regression (QR) SRC methods. Then, sediment yield values were obtained from 20-year discharge data (1992–2011). Despite the high uncertainty of QR results, the annual sediment delivery values of the models were achieved in an acceptable range. The most likely (with a probability of 0.5) average annual SSL values were between 713 × 103 and 840 × 103 ton for Shirgah–Talar station. Those values for Valikbon station were between 3142 × 101 and 3702 × 101. Moreover, the estimated average sediment yield in Shirgah–Talar station using MPSIAC and EPM were 591392 and 514054 ton/year, respectively. Those values for Valikbon station were 51881 and 27449 ton/year. Then, the results proved the better performance of MPSIAC in estimating SSL in the study area compared with EPM.

Soil salinity is a critical environmental problem especially in arid and semiarid regions. Then, the objective of this study is to detect saline soils by synergistic use of the Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Moderate Resolution Imaging Spectroradiometer (MODIS) images. In this regard, the Total Precipitable Water (TPW) Vapor parameter obtained from AMSR2 and MODIS, the Microwave Polarization Difference Index (MPDI), and a vertical to horizontal brightness temperature ratio ( T B v / T B h ) in the 6 GHz channel of AMSR2 were used in two procedures. In procedure 1, the thresholding on the TPW and MPDI, and in procedure 2, the thresholding on the TPW and the T B v / T B h in the 6 GHz channel were investigated. The overall accuracy and Kappa coefficient of the produced saline soil map by the procedure 1 were acquired as 0.865 and 0.715, and for the procedure 2 were 0.809 and 0.607, respectively.