Soil resilience assessment using soil profile descriptions and Analytic Hierarchy Process in Mediterranean mountains considering diverse fire occurrences

Wildfires are complex natural phenomena that exert significant impacts on landscapes,societies,and economies.Understanding the concept of resilience is crucial in mitigating its possible negative impacts,as it involves preparing for,responding to,and recovering from wildfires.This research aims to demonstrate the utility of in situ soil profile description in assessing land use resilience using an Analytic Hierarchy Process(AHP)through an expert panel survey.The study examines a catchment located in the Balearic Islands,considering two fire occurrences(once and twice),comparing abandoned agricultural terraces and natural hillslopes.The results demonstrated that the priority ranking of variables to assess soil profile resilience against wildfires,determined by a panel of 10 experts,identified horizon depth(25.1%),slope inclination(21.5%),and hydrological connectivity(16.6%)as the most crucial factors.Other variables,such as number and size of roots,structure of pedal soil material,size class structure,and rock fragments,also contributed to resilience but to a lesser extent,with scores ranging from 5.7%to 9.6%.Analyzing the priorities established by the experts using AHP,the results showed that the least resilient soil horizon was H1 of the control hillslope,especially under high and low connectivity processes,which aligned with the loss of superficial soil horizons after one and two wildfires.Hillslopes showed greater changes in resilience after occurring wildfires compared to terraces,with the most significant alterations occurring after the second wildfire event.This study addresses a significant knowledge gap in the field by highlighting the interconnectedness of wildfires,resilience,and land use,providing insights into land management strategies for wildfire-prone regions.

Using fuzzy-AHP and parametric technique to assess soil fertility status in Northeast of Iran

A good understanding of the levels and distribution patterns of soil properties and/or quality indicators is a prerequisite for developing sustainable agricultural land management programs. Traditional assessments of these parameters of soil fertility status are somewhat costly, in both economics and time aspects. Different modelling techniques have been proposed as a useful tool for determination of soil quality indicators and development of soil fertility maps, but to what extent these results are reliable remains under-quantified in many regions worldwide. To address this uncertainty, Fuzzy-Analytical Hierarchy Process(Fuzzy-AHP) and Parametric analyses were conducted to ascertain the soil fertility status of a semiarid region in the Northeast of Iran for some selected crops: alfalfa, corn silage, potato, sugar beet, tomato and wheat. The Fuzzy-AHP and Parametric techniques using soil suitability indices were estimated for each crop and each soil delineation was achieved by Ordinary Kriging. The Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS) was used as a compensatory method to allow tradeoffs among the selected criteria. Our results demonstrated that from the Fuzzy-AHP analysis, the soil fertility indices ranged from moderate to high for production of alfalfa;from low to high for production of corn silage and sugar beet;moderate to high for production of potato and tomato;and from low to moderate for production of wheat. However, the parametric analysis showed soil fertility classes ranging from very low to high for production of all the selected crops. High correlations were also observed between soil fertility indices predicted by both models. Similarly, the capacities of both models to predict soil fertility status for production of the selected crops were also highly correlated. The preference for the cultivation of the selected crops based on the Fuzzy-AHP analysis was sugar beet > corn silage > wheat > alfalfa > tomato > potato. On the other hand, using Parametric techniques, the crops preferences for cultivation ranked as corn silage > wheat > alfalfa > sugar beet > tomato > potato. We concluded that the findings would help to develop sustainable plans of cultivation based on patterns related to soil fertility classes depending on each crop’s requirement.

Evaluating the applicability of the water erosion prediction project(WEPP)model to runoff and soil loss of sandstone reliefs in the Loess Plateau,China

Soil erosion is one of the most serious environmental issues,especially in vulnerable areas such as the Pisha sandstone regions located in the Loess Plateau(China).In these types of reliefs,long-term studies monitoring runoff and soil loss are scarce,and even more considering the efficiency of different soil management techniques applied to reduce land degradation.In this study,seven years(2014-2020)of in-situ measurements of surface runoff and soil loss for different land uses(forestland,shrubland,grassland,farmland,and bare land)in a Pisha Sandstone environment at the Loess Plateau were con-ducted.We applied the Water Erosion Prediction Project(WEPP)model combining the large database with the precipitation regimes.Our results showed that runoff volume coming from observed and simulated data exhibited significant differences among them depending on the different vegetation types.Runoff and soil loss were different among diverse land use types as follows:farmland>grassland>shrubland>forestland.After conducting a calibration,we found satisfactorily simulated surface runoff and sediment yield based on precipitation regimes and land uses at sandstone reliefs.Simulation performance of surface runoff was better than sediment yield.The range of standard error of the model simulation for event and annual values of runoff were 4.71 mm and 12.19 mm,respectively.The standard error for event and annual values of soil loss were 4.19 t/hm^(2)and 21.86 t/hm^(2).In the calibration group,R2 of runoff and soil loss were 0.92 and 0.86 respectively,while Nash-Sutcliffe coefficient(E)reached 0.90 and 0.85,respectively.In the validation group,the R2 for both runoff and soil loss were 0.82 and 0.56,respectively.Nash-Sutcliffe coefficient(E)were 0.77 and 0.54 for the runoff and sediment yield.We concluded that using a detailed monitoring dataset,the WEPP model could accu-rately simulate and predict water erosion in the hillslopes of Pisha sandstone area.

Mapping sediment mobilization risks:Prioritizing results obtained at watershed and sub-watershed scales

Soils are key natural resources for the Earth's system;however,human impacts,especially,soil erosion are considered serious threats.Therefore,identifying and assessing effective factors to understand erosion hot spots at different scales is critical to developing effective land management plans and ensuring the sustainability of the territory.This study was conducted to determine and prepare an erosion risk map,but to prioritize the survey at different scales,such as sub-basin and watershed ones.To achieve this goal,geographic information system(GIS)and remote sensing data(RS)were used combining the analysis network process method(ANP)and ICONA model(Institute for the Conservation of Nature).As study case,we selected the degraded areas of the Gorganrood watershed located in the north of Iran.The study area was obtained for very low,low,medium,high,and very high-risk classi-fications of 14.0,21.4,17.9,31.3,and 15.4%,respectively.Results from the ICONA model also indicated that 12.8,28.8,22.1,27.9,8.5,and 0.03%belong to very low,low,medium,high,very high,and without risk of erosion,respectively.According to the validation results,it was found that the accuracy of ANP and ICONA models are 0.83 and 0.80,respectively,which indicates the suitability of the models for preparing the erosion map of the region is appropriate and useful for designing land management plans.We conclude that both models can be used to develop the erosion map potential and to prioritize sub-basins if a complete database of geomorphological characteriscs and human activities are accurate previously defined.