Development and analysis of the Soil Water Infiltration Global database

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements ( ∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76% of the experimental sites with agricultural land use as the dominant type ( ∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it

Dynamic Analysis Of Soil Erosion-Based Watershed Health

Accelerated soil erosion is one of the most important detrimental factors affecting the quality of the watershed health. Due to different environmental pressures and drivers, the effort is needed for ecological health and resilience assessment in regards to erosion changeability. However, this important subject has not been adequately studied yet. Towards this, in the present research, an innovative approach was developed for conceptualizing the watershed health dynamics in viewpoint of soil erosion. A risk-based study was conducted to quantitatively characterize the spatiotemporal variability of erosion-based health in an industrialized watershed i.e., the Shazand Watershed using the conceptual reliability, resilience and vulnerability (RelResVul) framework for four node years of 1986, 1998, 2008 and 2014. To this end, the soil erosion was estimated at monthly scale in 24 sub-watersheds by applying the Revised Universal Soil Loss Equation (RUSLE). The RelResVul indicators were then computed according to the threshold defined for the study watershed. A geometric mean was used to combine the three risk indicators and the erosion-based watershed health index was ultimately calculated for each study sub-watershed. Additionally, the change detection analysis was conducted over the years of 1986 to 2014. According to the results of erosion-based the RelResVul indices, very healthy, healthy, moderately healthy, unhealthy and very un-healthy conditions in the Shazand Watershed were respectively distributed over some 67, 25, zero, zero and eight percent for 1986; 50, 13, eight, zero and 29 % for 1998; 71, eight, 83, zero, zero and eight percent for 2008 and finally 71, zero, 17, zero and 12 % for 2014. The results of change detection revealed an oscillating trend of erosion-based watershed health index during the whole study period (1986 -2014). So that, during periods of 1986-1998, 1986-2008 and 1986-2014, the watershed health decreased at tune of 23, 13 and six percent, respectively. Whilst, the watershed health improved during study periods of 1998-2008 (13 %), 2008-2014 (eight percent) and 1998-2014 (22 %). The results also identified ‘hot spots’ of the most important index of land degradation and ‘bright spots’ of land improvement in the Shazand Watershed.The proposed approach would provide a sustainable framework supporting decision makers to comprehend health-related soil erosion targets according to the integrated watershed management plans

LAND COVER BASED WATERSHED HEALTH ASSESSMENT

The adoption of appropriate managerial approaches mainly depends upon propermonitoring and consequent assessment of ecosystems health. Towards that, thewatershed health monitoring has gained recognition among regulating agenciessuch as Environmental Protection Agency (EPA). However, its importance has notbeen considerably taken into account by authorities in developing countries wherethe outcome of such approach is essentially needed for effective and efficientmanagement of the ever-degrading ecosystems. To this end, the present articleintroduces a simple and standardized approach of describing the overall watershedhealth situation using risk based RelResVul framework. Towards this, threeindicators of reliability (Rel), resilience (Res) and vulnerability (Vul) have beenconceptualized and calculated based on the normalized difference vegetation index(NDVI) for the Shazand Watershed, Markazi Province, Iran, as a case study. NDVIis an important and commonly used vegetation index in research on globalenvironmental change. The primary data collected to create NDVI maps was multispectralsatellite images of path 165 and rows of 36 and 37, with a spatialresolution of 30 m from the Landsat Satellite images for the sample year of 2014.The results of RelResVul analysis showed that the overall condition of the ShazandWatershed health in terms of Rel, Res and Vul was healthy, un-healthy andmoderately healthy, respectively with scores of 0.82, 0.17 and 0.50 out of 1.0. Theaverage watershed health index based on RelResVul framework was also obtained0.34 varying from 0.04 to 0.46. Hence, it can be concluded that the ShazandWatershed was in relatively un-healthy state from view of vegetation cover. Themaintenance and recovery of the Shazand Watershed health should be consideredas fundamental step to reach the integrated watershed management objectives

Influence of freeze-only and freezing-thawing cycles on splash erosion

Soil erosion is recognized as one of the most important types of land degradation in the world particularly in many developing countries like Iran. Water erosion is initiated by splash erosion triggered by raindrop impact. Understanding the process of splash erosion under freezing and thawing conditions is essential to unravel soil erosion mechanisms under temperate conditions leading to appropriate planning of soil and water conservation projects. The present study aimed to study the individual effects of freeze-only as well as freezing-thawing cycle on splash erosion in a loess soil from an erosion prone area in mountainous northern regions of Iran. The study was conducted under laboratory conditions using erosion plots. The erosion plots were subjected to freeze only and freeze-thawing treatments by simulating cold conditions using a large cooling compartment system specifically manufactured for this purpose. The splash erosion under a designed simulated rainfall (1.2 mm min−1 for 30 min) was then measured as upward, downward and net splash erosion in splash cups. The results showed that freeze only decreased the upward, downward and net splash erosion by 0.81 ± 0.43, 0.82 ± 0.29 and 0.85 ± 0.23% while freezing-thawing cycle decreased splash erosion to 0.93 ± 0.83, 0.61 ± 0.43 and 0.57 ± 0.36%. This may be attributed to temporary increase in soil strength and stability or surface sealing during freezing process leading to reduced splash erosion. Keywords: Experimental plots, Freezing effects, Rainfall simulation, Soil detachment proces

Hydrological Drought Severity in Different Return Periods in Rivers of Ardabil Province, Iran

Hydrological drought (HD) characterization with different return periods is essential to appropriately design the best water management practices. In particular, characterizing the interactive relations of discharge, drought, and return periods using a novel triple diagram can deepen the interpretation of regional droughts, which have not been adequately considered, especially in semi-arid areas. Considering the critical role of HD in water exploitation and management in Iran, this study was therefore conducted to analyze the HD in different return periods in rivers of the Ardabil Province (area = 17,953 km2). To this end, the streamflow drought index (SDI) was computed using DrinC software at 1-, 3-, and 6-month time scales for 25 hydrometric stations during 1981–2014. Then, the drought severity was evaluated by CumFreq software in different return periods (2, 5, 10, 25, 50, and 100 years). Finally, the relationship between discharge, SDI, and return periods was analyzed using triple diagram models. The results revealed that the drought events had mild (−1 ≤ SDI < 0) and moderate (−1.5 ≤ SDI < −1) severity for most study stations in the study area. The mean values of SDI in the 1-, 3-, and 6-month time scales were 1.08, 0.80, and 0.55, respectively. At all study time scales, the drought severity in both rivers with low and high flows increased with increasing return periods. In such a way, the maximum drought severity has been found for rivers with high flow at a 100-year return period. The current results can be considered a screening tool for the distinctive conservation and directive management of watershed resources

Spatial Comparative Analysis of Landscape Fragmentation Metrics in a Watershed with Diverse Land Uses in Iran

Knowledge of landscape fragmentation is known to be important in ecological integrity, hydrological processes, urban planning, sustainable land management, and policymaking. Recent anecdotal studies reveal a need for analytical quantification of landscape fragmentation at different levels. Therefore, the present study was conducted at KoozehTopraghi Watershed, Ardabil Province, Iran, where covers by different land uses/covers, to (a) explore the spatial pattern of landscape fragmentation metrics comprehensively in different scales, (b) distinguish the landscape fragmentation hot spots, and (c) investigate the spatial clustering of landscape fragmentation metrics. The behaviors of 7, 10, and 13 fragmentation metrics concerning three levels of patch, class, and landscape across 36 sub-watersheds were explored using principal component analysis (PCA) and expert elicitation. The Getis-Ord Gi* and local Moran’s I indices were also used to analyze the hot spots and clusters of landscape fragmentation, respectively. The results verified the high degree of spatial variability of the metrics in the three levels of fragmentation analysis. The class-level fragmentation analysis showed that the watershed is characterized by high-fragmented residential land use and low-fragmented dry farming land use. The spatial trend analysis at the landscape level further indicated that sub-watersheds 1, 2, 11, 21, to 26, and 34 to 36, mainly located in lowlands and central parts, allocated better status considering the fragmentation metrics rather than other parts of the watershed. The significant hot spots and high clusters of fragmentation also were distributed in different parts of the watershed in terms of various landscape metrics

Leaf Area Index Variations in Ecoregions of Ardabil Province, Iran

The leaf area index (LAI) is an important vegetation biophysical index that provides broad information on the dynamic behavior of an ecosystem’s productivity and related climate, topography, and edaphic impacts. The spatiotemporal changes of LAI were assessed throughout Ardabil Province—a host of relevant plant communities within the critical ecoregion of a semi-arid climate. In a comparative study, novel data from Google Earth Engine (GEE) was tested against traditional ENVI measures to provide LAI estimations. Moreover, it is of important practical significance for institutional networks to quantitatively and accurately estimate LAI, at large areas in a short time, and using appropriate baseline vegetation indices. Therefore, LAI was characterized for ecoregions of Ardabil Province using remote sensing indices extracted from Landsat 8 Operational Land Imager (OLI), including the Enhanced Vegetation Index calculated in GEE (EVIG) and ENVI5.3 software (EVIE), as well as the Normalized Difference Vegetation Index estimated in ENVI5.3 software (NDVIE). Moreover, a new field measurement method, i.e., the LaiPen LP 100 portable device (LP 100), was used to evaluate the accuracy of the derived indices. Accordingly, the LAI was measured in June and July 2020, in 822 ground points distributed in 16 different ecoregions-sub ecoregions having various plant functional types (PFTs) of the shrub, bush, and tree. The analyses revealed heterogeneous spatial and temporal variability in vegetation indices and LAIs within and between ecoregions. The mean (standard deviation) value of EVIG, EVIE, and NDVIE at a province scale yielded 1.1 (0.41), 2.20 (0.78), and 3.00 (1.01), respectively in June, and 0.67 (0.37), 0.80 (0.63), and 1.88 (1.23), respectively, in July. The highest mean values of EVIG-LAI, EVIE-LAI, and NDVIE-LAI in June are found in Meshginshahr (1.40), Meshginshahr (2.80), and Hir (4.33) ecoregions and in July are found in Andabil ecoregion respectively with values of 1.23, 1.5, and 3.64. The lowest mean values of EVIG-LAI, EVIE-LAI, and NDVIE-LAI in June were observed for Kowsar (0.67), Meshginshahr (1.8), and Neur (2.70) ecoregions, and in July, the Bilesavar ecoregion, respectively, with values of 0.31, 0.31, and 0.81. High correlation and determination coefficients (r &gt; 0.83 and R2 &gt; 0.68) between LP 100 and remote sensing derived LAI were observed in all three PFTs (except for NDVIE-LAI in June with r = 0.56 and R2 = 0.31). On average, all three examined LAI measures tended to underestimate compared to LP 100-LAI (r &gt; 0.42). The findings of the present study could be promising for effective monitoring and proper management of vegetation and land use in the Ardabil Province and other similar areas

Multisensor assessment of leaf area index across ecoregions of Ardabil Province, northwestern Iran

Leaf area index (LAI), one of the most crucial vegetation biophysical variables, is required to evaluate the structural characteristic of plant communities. This study, therefore, aimed to evaluate the LAI of ecoregions in Iran obtained using Sentinel-2B, Landsat 8 (OLI), MODIS, and AVHRR data in June and July 2020. A field survey was performed in different ecoregions throughout Ardabil Province during June and July 2020 under the satellite image dates. A Laipen LP 100 (LP 100) field-portable device was used to measure the LAI in 822 samples with different plant functional types (PFTs) of shrubs, bushes, and trees. The LAI was estimated using the SNAPv7.0.4 (Sentinel Application Platform) software for Sentinel-2B data and Google Earth Engine (GEE) system–based EVI for Landsat 8. At the same time, for MODIS and AVHRR, the LAI products of GEE were considered. The results of all satellite-based methods verified the LAI variations in space and time for every PFT. Based on Sentinel-2B, Landsat 8, MODIS, and AVHRR application, the minimum and maximum LAIs were respectively obtained at 0.14–1.78, 0.09–3.74, 0.82–4.69, and 0.35–2.73 for shrubs; 0.17–5.17, 0.3–2.3, 0.59–3.84, and 0.63–3.47 for bushes; and 0.3–4.4, 0.3–4.5, 0.7–4.3, and 0.5–3.3 for trees. These estimated values were lower than the LAI values of LP 100 (i.e., 0.4–4.10 for shrubs, 1.6–7.7 for bushes, and 3.1–6.8 for trees). A significant correlation (p 0.63 and R2 > 0.89), Landsat 8 (|r| > 0.50 and R2 > 0.72), MODIS (|r| > 0.65 and R2 > 0.88), and AVHRR (|r| > 0.59 and R2 > 0.68). Due to its high spatial resolution and relatively significant correlation with terrestrial data, Sentinel-2B was more suitable for calculating the LAI. The results obtained from this study can be used in future studies on sustainable rangeland management and conservation

Changeability of reliability, resilience and vulnerability indicators with respect to drought patterns

Climate-related extremes such as droughts have led to significant impacts on some watersheds. To assess watershed health and develop effective management plans, information about the function and structure of the watersheds in the context of their climatic response, especially to take into account rainfall anomalies and climate change adaptation, is needed. Integration of climatic variables with reliability, resilience and vulnerability (RRV) indicators, is a novel approach for generating this information. This study investigated the behavior of RRV indicators with respect to rainfall variability and drought patterns for three watersheds governed by different climates. Reliability was defined as the probability of a watershed to be in the range of satisfactory Standardized Precipitation Index (SPI) values. Resilience was indicated as the speed of recovery from an unsatisfactory condition. Vulnerability was defined as a function of the exposure of a watershed to climate change and variation using the SPI. The study areas were the Foyle Watershed in Northern Ireland (temperate oceanic, Cfb), the Xarrama Watershed in Portugal (Mediterranean hot summer, Csa) and the Shazand Watershed in Iran (moderate to cold semi-arid (Bsk). Based on the SPI pattern of each watershed, the SPI of −0.1 for the Foyle and Xarrama watersheds and +0.1 for the Shazand Watershed was selected as the drought threshold. The drought based RRV index was subsequently calculated from long-term (1981–2012) RRV indicators, resulting in means of 0.52 ± 0.25, 0.53 ± 0.21 and 0.30 ± 0.18 for the three watersheds, respectively. These means reflect the status of the watersheds in terms of climatic conditions, which was moderate dry (0.41–0.60) for the Foyle and Xarrama watersheds and dry (0.21–0.40) for the Shazand Watershed. The temporal trend of the drought based RRV index was found to be non-significantly increasing (P-value >0.52) for the Foyle and Xarrama watersheds and non-significantly decreasing for the Shazand Watershed (P-value >0.48). The vulnerability indicator and drought based RRV index were significantly (p-value = 0.00) affected by the climatological gradient. The results of the conceptual framework linked to statistical trends can provide researchers, policy makers, and land managers a more comprehensive base to assess variability of watershed health and design drought management plans

Assessing the hydrological effects of land-use changes on a catchment using the Markov chain and WetSpa models

Gyasi-Agyei, Y ORCiD: 0000-0002-2671-1180Predicting the effects of land-use (LU) changes and hydrological processes on a rapidly urbanized catchment using the Markov chain and WetSpa models is the main objective of this research. Hourly hydrometeorological data for 2001–2016, land use maps, a digital elevation model (DEM) and soil texture were used as inputs into the models. The simulation results verified some negative impacts of LU changes, such as increases in peak discharge and flow velocity from 2001 to 2032 by 57.1% and 39.4%, respectively. Additionally, the time of concentration decreased from 6 h in 2001 to 5 h in 2016 and to 4 h in 2032. Surface runoff recorded the highest increases by 48.4% and 83.9%, respectively, in 2016 and 2032, compared to 2001. We concluded that the combination of both models is an appropriate tool for predicting the possible effects of LU changes on different hydrological features, which provide vital information for land managers. © 2020, © 2020 IAHS