Soil Salinity In Arid Regions Research Articles

Effect of Autumn Irrigation on Salt Leaching under Subsurface Drainage in an Arid Irrigation District

Non-growing season irrigation and farmland subsurface drainage play a crucial role in salt leaching and salinization control in arid irrigation areas. This study aimed to investigate the reduction of autumn irrigation quotas and drainage discharge while maintaining soil moisture retention and reducing soil salinization. Field experiments were conducted with different autumn irrigation quotas (160 mm for SD1, 180 mm for SD2, and 200 mm for SD3) combined with subsurface drainage (1.5 m drain depth and 45 m spacing). A control treatment (referred to as CK) without subsurface drainage received 200 mm of irrigation. The results showed that, after 31 days of autumn irrigation, the groundwater depth in all three subsurface drainage plots stabilized to 1.5 m, with the CK being 0.2–0.3 m shallower compared to the SD plots. The mean soil water content in the 0–150 cm soil layer of the SD1, SD2, SD3, and CK after autumn irrigation was 0.36, 0.39, 0.41, and 0.42 cm3cm−3, respectively. The combination of autumn irrigation and subsurface drainage significantly reduced the soil salt content. The mean desalination rates in the root zone (0–60 cm) soil layer were 57.5%, 53.7%, 51.9%, and 45.1% for the SD3, SD2, CK, and SD1, respectively. The mean desalination rate of 60–150 cm was not significantly different between the SD2 and SD3 (p > 0.05), and both were significantly higher than that of the SD1 and CK (p < 0.05). The drainage discharge was 31, 36, and 40 mm in the SD1, SD2 and SD3, respectively. The amount of salt discharge through the drain pipe increased with increasing irrigation quota, which was 1.22 t/ha, 1.41 t/ha, and 1.50 t/ha for the SD1, SD2, and SD3, respectively. Subsurface drainage is an effective way to prevent salt accumulation in the soil, and an autumn irrigation quota of 180 mm is recommended for leaching of salinity in the Hetao Irrigation District. These findings provide valuable insights into optimizing irrigation practices and managing soil salinization in arid regions.

Reconciling crop production and ecological conservation under uncertainty: A fuzzy credibility-based multi-objective simulation-optimization model

To cope with the problems of agricultural water conflicts and secondary soil salinization in arid regions, a fuzzy credibility-based multi-objective simulation-optimization model is proposed for optimizing irrigation water allocation and crop area planning under uncertainty. This model combines simulation module of enabling to quantify daily physical process of water-salt movement among soil water, crop root zone and groundwater aquifers, optimization module of managing water resources and fuzzy credibility-constrained programming into a general framework. It's applied to a case study in the Jiefangzha Irrigation Subarea in Hetao Irrigation District, Northwest China. Three objectives encompassing maximizing net economic benefits, maximizing nutritional water productivity and minimizing carbon emissions from agricultural system are interconnected through decision variables. Four credibility scenarios of fuzzy constrains including β = 0.6 to 0.9 are presented for obtaining decision-making solutions. Through NSGA-III, such a high-dimensional multi-objective problem is solved. This study uses the multi-objective constraint-handling strategy to handle constraints, which exploits the effective information within infeasible solutions. Moreover, it emphasizes the importance of soil water-salt movement processes in determining optimal solutions and helps decision makers weigh the system outputs and risk level of violating constraints. Results illustrate that when β increases from 0.6 to 0.9, net economic benefit decreases from 1.742 × 109 Yuan to 1.706 × 109 Yuan, nutritional water productivity decreases from 9136.0 kcal/m3 to 8819.6 kcal/m3, and carbon emissions increase from 439.6 × 106 kg. C to 441.6 × 106 kg.C, which shows that an increasing credibility level leads to lower system benefits and conservative system outputs. The results can provide valuable information for managing irrigation water resources and controlling salinity accumulation. Furthermore, dynamic decisions related to water-salt movement processes can be readily generated. These findings show that the developed approach is globally applicable for managing irrigation water in arid and semiarid regions that face similar problems.

Spatial variability of salt content caused by nonuniform distribution of irrigation and soil properties in drip irrigation subunits with different lateral layouts under arid environments

The nonuniformity of drip irrigation that is highly dependent on lateral layouts has been a concern for secondary soil salinization in arid regions. The effects of spatial variabilities in drip irrigated water and soil properties on soil salt content (SSC) distribution were therefore evaluated at a typical operational scale of subunits for a drip irrigation system. Two types of subunits with different lateral layouts, one with single end feeding laterals (S1) and one with dual-end feeding laterals (S2), were investigated during the 2018 and 2019 growing seasons of mulch drip irrigated cotton under arid environments. The distribution of the irrigation amount and SSC at the initial stage (prior to the first drip irrigation) and during the boll opening stage of cotton and the soil particle size distribution and bulk density in the subunits with different water feeding modes were determined. The results revealed that the Christianson uniformity coefficients (CUs) of the emitter discharge rate for S2 were 4–7% higher than those for S1, even when the area of S2 was 1.5 times that of S1. The more nonuniformly distributed irrigation water for S1 produced a more dispersed distribution of SSC, with CV ranging from 0.23 to 0.82, which was noticeably higher than the range of 0.13–0.34 for S2. The partial least squares analysis results demonstrated that the importance of the factors on the spatial variability of SSC followed an order of initial SSC > drip irrigation water > soil physical properties for S1 and initial SSC > soil physical properties > drip irrigation water for S2. The dual-end water feeding mode reduced the potential effect of the nonuniformity of irrigation water on SSC due to the improved uniformity on the subunit scale. Our study suggests that the dual-end feeding mode would be promising to avoid local salt harmfulness caused by the nonuniformity of SSC in the drip irrigation system.

Evaluation of the Efficiency of Spectral Data and Indices Derived from OLI and TIRS Sensors in Estimating Soil Salinity in Arid Regions of Southern Ilam Province

شوری خاک یکی از مشکلات مهم زیست‌محیطی است و شناسایی و پهنه‌‌بندی خاک‌های شور، به‌علت نیاز به نمونه‌برداری و انجام‌دادن آنالیزهای آزمایشگاهی و همچنین تغییرپذیری زمانی و مکانی آن، مشکل است. در سال‌های اخیر استفاده از تصاویر ماهواره‌ای، به‌علت استفادة آسان و توانایی در شناسایی پدیده‌ها، همواره مورد توجه متخصصان قرار گرفته است. در این پژوهش، 220 نمونة خاک از منطقة میمة شهرستان دهلران، در جنوب استان ایلام، با توجه به نوع مطالعه و تیپ‌های فیزیوگرافی و واحدهای متشکل خاک‌ها برداشت شد. سپس مقادیر pH و EC با استفاده از روش‌های استاندارد اندازه‌گیری‌ شد. ارزیابی مقادیر شوری خاک، با استفاده از روابط همبستگی بین مقادیر هدایت الکتریکی EC حاصل از داده‌های زمینی، با متغیرهای به‌دست‌آمده از تصاویر ماهواره‌ای لندست 8 شامل باندها، شاخص‌های شوری، شاخص‌های پوشش گیاهی و شاخص‌های خاک صورت گرفت. در نهایت، مدل تخمین شوری سطحی خاک با روش رگرسیون گام‌به‌گام به‌دست آمد. این روش شامل انتخاب خودکار متغیرهای مستقل است و با دردسترس‌بودن بسته‌های نرم‌افزاری آماری، انجام‌دادن آن حتی در مدل‌هایی با صدها متغیر امکان‌پذیر است. در مطالعات گذشته، شاخص‌ها و باندها به‌صورت جداگانه و محدود به‌کار رفته‌اند اما، در این مطالعه، سعی شده است از ترکیب شاخص‌های گوناگون استفادة گسترده‌تری شود و در نهایت، با حذف شاخص‌هایی که کمترین تأثیر را در برآورد شوری خاک داشته‌اند، بهترین مدل برآورد شوری برای خاک منطقه پیشنهاد شد. با استفاده از آنالیز سطح معنی‌داری و میزان همبستگی بین خروجی مدل‌ها و داده‌های زمینی، بهترین مدل با مقدار (882/0R2=) انتخاب و نقشة شوری خاک براساس آن تهیه شد. بیشترین مساحت مربوط به کلاس غیرشور است که 75% از کل منطقة مورد مطالعه را شامل می‌شود و حدود 1% از خاک‌های منطقه نیز مربوط به کلاس بسیار شور است. با مقایسة داده‌های حاصل از ماهوارة لندست 8 و به‌کارگیری شاخص‌ها و قراردادن شاخص‌ها در معادلة رگرسیونی گام‌به‌گام، این نتیجه حاصل شد که تصاویر ماهواره‌ای برای ارزیابی شوری خاک منطقه کارآمد است و نتایج حاصل، همبستگی بالایی در سطح 88/0 با داده‌های زمینی دارند.

Comparing the effect of different irrigation water scenarios on arid region pecan orchard using a system dynamics approach

Water scarcity and soil salinization in arid regions have made desalination a competitive alternative source for irrigation. Perceptions of a higher cost and other misconceptions about desalinated water have limited its broader usage in agriculture. In this study, we have focused on understanding the suitability of using desalinated water as a substitute for saline water in the pecan (Carya illinoinensis) orchards of southwest Texas. Pecan is a perennial high-value nut crop that cannot be easily replaced. Therefore, it represents a perfect case study for the application of desalinated water. A recently developed system dynamic model, SMITUV (System Dynamic Modeling of Infiltration, Solute Transport, and Root Water Uptake in Vadose Zone), was modified to assess the effects of irrigation with desalinated water when soil-water salt content increased above pecan tolerance levels. This model simulated five irrigation scenarios with different fractions of river water and saline groundwater. As expected, to sustain the same level of pecan production, a higher amount of desalinated water was needed with increasing amounts of groundwater in the irrigation mix. Soil texture had a significant influence on the amount of desalinated water required. For sandy and silty soils, the 100% river water scenario required no additional desalinated water. Clayey soils could not sustain high production even in a 100% river water scenario. An economic analysis showed that pecan operations might be viable in non-clayey regions for some irrigation mixture even after factoring in the cost of using desalinated water. However, current desalination techniques and associated costs were economically unviable for sustaining pecan in regions with saline groundwater and clayey soils. This study also demonstrated the application of SMITUV and system dynamic modeling as a decision-making tool to assist growers in understanding the farm-scale applicability of desalinated water.

Ground Observations and Environmental Covariates Integration for Mapping of Soil Salinity: A Machine Learning-Based Approach

Soil salinization is a severe danger to agricultural activity in arid and semi-arid areas, reducing crop production and contributing to land destruction. This investigation aimed to utilize machine learning algorithms to predict spatial soil salinity (dS m−1) by combining environmental covariates derived from remotely sensed (RS) data, a digital elevation model (DEM), and proximal sensing (PS). The study is located in an arid region, southern Iran (52°51′–53°02′E; 28°16′–28°29′N), in which we collected 300 surface soil samples and acquired the spectral data with RS (Sentinel-2) and PS (electromagnetic induction instrument (EMI) and portable X-ray fluorescence (pXRF)). Afterward, we analyzed the data using five machine learning methods as follows: random forest—RF, k-nearest neighbors—kNN, support vector machines—SVM, partial least squares regression—PLSR, artificial neural networks—ANN, and the ensemble of individual models. To estimate the electrical conductivity of the saturated paste extract (ECe), we built three scenarios, including Scenario (1): Synthetic Soil Image (SySI) bands and salinity indices derived from it; Scenario (2): RS data, PS data, topographic attributes, and geology and geomorphology maps; and Scenario (3): the combination of Scenarios (1) and (2). The best prediction accuracy was obtained for the RF model in Scenario (3) (R2 = 0.48 and RMSE = 2.49), followed by Scenario (2) (RF model, R2 = 0.47 and RMSE = 2.50) and Scenario (1) for the SVM model (R2 = 0.26 and RMSE = 2.97). According to ensemble modeling, a combined strategy with the five models exceeded the performance of all the single ones and predicted soil salinity in all scenarios. The results revealed that the ensemble modeling method had higher reliability and more accurate predictive soil salinity than the individual approach. Relative improvement (RI%) showed that the R2 index in the ensemble model improved compared to the most precise prediction for the Scenarios (1), (2), and (3) with 120.95%, 56.82%, and 66.71%, respectively. We applied the best model in each scenario for mapping the soil salinity in the selected area, which indicated that ECe tended to increase from the northwestern to south and southeastern regions. The area with high ECe was located in the regions that mainly had low elevations and playa. The areas with low ECe were located in the higher elevations with steeper slopes and alluvial fans, and thus, relief had great importance. This study provides a precise, cost-effective, and scientific base prediction for decision-making purposes to map soil salinity in arid regions.

Effects of Biochar on Infiltration and Evaporation of Soil Water with Sand Mulching

Water shortages and soil salinization in arid regions of northwestern China have become an important factor limiting agricultural production and affecting the living conditions of farmers. Using existing water resources and salinized land scientifically and efficiently is important for improving agricultural production. We studied the characteristics of the infiltration and evaporation of soil water under the application of different amounts of biochar in indoor soil-column simulations with sand mulching to determine the effect of biochar on the infiltration and evaporation of soil water. We tested five treatments: sand mulching with no biochar (CK) and sand mulching with 0.5, 1.5, 2.5 and 4.5% biochar. Cumulative infiltration and the rate of migration of the wetting front were higher with 0.5 and 1.5% biochar and lower with 2.5 and 4.5% biochar than CK, respectively. The distance and duration of migration of the wetting front followed the power function F = a·tb, a relationship consistent with the Kostiakov model of infiltration. The cumulative evaporation of soil water was higher with 0.5 and 1.5% biochar and lower with 2.5 and 4.5% biochar than CK. The variation of cumulative evaporation was represented well by both the Black and Rose models of evaporation. The results of this study have important implications for the application of biochar in arid regions of northwestern China for improving the hydrological characteristics of soil in agricultural practices.

Improving the spatial prediction of soil salinity in arid regions using wavelet transformation and support vector regression models

The low potential of agricultural productivity in the majority of central Iran is mainly attributed to high levels of soil salinity. To increase agricultural productivity, while preventing any further salinization, and implement effective soil reclamation programs, precise information about the spatial patterns and magnitude of soil salinity is essential. In this study, soil salinity was predicted and mapped using machine learning (ML) and digital soil mapping approaches. Specifically, support vector regression (SVR) was combined with wavelet transformation (W-SVR) of a wide range of environmental covariates derived from a digital elevation model, remote sensing, and climatic data. Predictions of soil salinity were carried out for six standard depth increments (0–5, 5–15, 15–30, 30–60, 60–100, 100–200 cm). Cross-validation was carried out by partitioning the data into 70% used for training the model and 30% for testing the model. Uncertainty of the ML algorithms was quantified using the uncertainty estimation based on local errors and clustering (UNEEC) method. The results indicated that W-SVR performed better in predicting soil salinity for all six depth increments. The differences were most apparent for the lowest soil depth increments where W-SVR resulted in ~1.4 times higher correlation coefficient when compared to the SVR. At lower soil depths increments, covariate importance analysis indicated that topographic derivatives were the most relevant covariates in the models. For topsoil salinity, remote sensing covariates were the most relevant predictors of soil salinity. Regardless of soil depth, climatic predictors were the most important predictors. Uncertainty analysis also indicated that for all depth increments, the estimated prediction interval for SVR obtained by the UNEEC method was wider than that of W-SVR and further indicating the higher performance of W-SVR in comparison to the SVR. The predicted salinity maps showed the highest salinity for soils in the eastern parts of central Iran, which was consistent with the Agro-climatic Zoning of Isfahan Province.

Enhanced electrokinetic removal of problematic salts in arid and semi-arid areas

Recently, soil salinization in arid regions has caused considerable damage to ecosystems, agricultural productivity, and civil engineering infrastructure and facilities. This threat has become one of the most hazardous environmental issues and is the main reason for land degradation, desertification, and reduced soil load-bearing capacities. Conventional techniques of mitigating soil salinization such as soil irrigation, soil substitution, planting salt-accumulating plants, and soil amendment are expensive, time-consuming, and ineffective. Thus, the remediation of salt-affected soils represents a new challenge in the mitigation of soil salinization in arid and semi-arid lands. In this work, the feasibility of an electrokinetic treatment that removes salts from saline soil was evaluated. Three experimental electrokinetic tests were conducted with a laboratory-made electrokinetic apparatus using deionized (DI) water as the working solution. The potential gradient was set to either 1.5, 2.0, or 2.4 V/cm. This range of values was chosen to ensure low energy consumption and to suppress heating, which has adverse effects on the treatment. An enhanced electrokinetic approach (EEA) was developed by investigating the effects of diiferent electrical applied voltages (EAVs) on the removal of salts. The results revealed that the salt concentration gradually decreased and the salt removal rate increased as the EAV was increased. The highest salt removal rate occurred with an EAV of 2.4 V/cm, which yielded removal efficiencies of 89% and 88% for calcium (Ca2+) and sulfate (SO42−) ions, respectively. This research shows that the proposed electrokinetic technique has the potential to highly efficiently remediate and reclaim problematic salt-affected soils in arid and semi-arid areas.

Using sequential Gaussian simulation to assess the uncertainty of the spatial distribution of soil salinity in arid regions of Northwest China

ABSTRACTAccurately mapping and monitoring the spatial distribution pattern of soil salinity is essential for sustainable soil management and decision-making. The kriging-based interpolation technique is generally used to map the spatial distribution of soil salinity; however, this technique neglects the variation caused by interpolation for each unsampled location. The sequential gaussian simulation (SGS) is an effective tool to collect mapping uncertainties at several locations simultaneously, which is not possible in the kriging-based technique. Soil electrical conductivity has been widely used as an index for soil salinity. Based on 0–100 cm soil profile from 117 locations in the Manas River basin, Northwest China, the SGS algorithm was used to assess the uncertainty of the spatial distribution of soil electrical conductivity. It was found that the SGS algorithm was reliable in reproducing the spatial distribution of soil electrical conductivity. The SGS algorithm reproduced the sample statistics reasonably well. The standard deviations of the samples generated by the SGS algorithm (0.463–0.508 (dS m−1)) were closer to the actual samples (0.675 (dS m−1)) than those generated by kriging (0.454 (dS m−1)). Most of the study area was lightly affected by salinity. Around 30% of the study area was moderately affected, and the heavily affected areas were sporadically scattered across the study area. The spatial uncertainty at multiple point presented a declining trend as the critical probability at a single point increased. The spatial estimation of the soil electrical conductivity in multiple point was more robust than that in the local location because of the low uncertainty.

三工河流域琵琶柴群落特征与土壤因子的相关分析

PDF HTML阅读 XML下载 导出引用 引用提醒 三工河流域琵琶柴群落特征与土壤因子的相关分析 DOI: 10.5846/stxb201210071379 作者: 作者单位: 中国科学院植物研究所,中国科学院植物研究所,中国科学院植物研究所,中国科学院植物研究所,中国科学院植物研究所,中国科学院植物研究所,中国科学院植物研究所,青城山-都江堰旅游景区管理局,青城山-都江堰旅游景区管理局,中国科学院植物研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点基础研究发展计划资助项目（2009CB825103） Correlation between characteristics of Reaumuria soongarica communities and soil factors in the Sangong River basin Author: Affiliation: Institute of Botany,Chinese Academy of Sciences,,Institute of Botany,Chinese Academy of Sciences,Institute of Botany,Chinese Academy of Sciences,Institute of Botany,Chinese Academy of Sciences,Institute of Botany,Chinese Academy of Sciences,Institute of Botany,Chinese Academy of Sciences,,,Institute of Botany,Chinese Academy of Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:琵琶柴（Reaumuria soongorica）是我国荒漠地区分布最广的地带性植被类型之一，对维系荒漠地区生态系统的稳定性具有重要作用。以三工河流域两个琵琶柴群落为对象，在2010年主要生长季节（6-10月），通过群落和土壤调查，采用土钻法、土柱法、地上收割法对两个琵琶柴群落的土壤性质、生物多样性、细根生物量、地上生物量、生物多样性与土壤性质的关系进行研究，结果表明：两个琵琶柴群落在冠幅、盖度、多度和物种多样性等方面均存在显著差异。在0-100 cm土壤层内，两个群落土壤电导率、pH值、容重、含水量存在显著差异。除土壤容重外，群落2各个土壤因子的值均大于群落1，并随土壤深度的增加表现出类似的趋势。两个群落物种多样性指数、地上生物量、细根生物量存在显著差异，从6月到10月呈现先下降再上升的趋势。由于7、8月群落1有大量夏雨型短命植物和类短命草本植物的出现，Shannon-Wiener多样性指数、Pielou均匀度指数急剧降低，Simpson指数表现出相反的变化趋势。群落2土壤电导率和pH值较高，草本植物鲜有出现，多样性指数和均匀度指数变化均较为平缓。两个群落的Sorenson相似性系数较低，群落差异明显。相关和回归分析表明土壤环境因子是导致两个琵琶柴群落特征、生物多样性和生物量不同的主要因素。较高的土壤含水量可以增加琵琶群落的生物多样性，较高的土壤容重抑制琵琶柴群落细根的生长，轻度的干旱胁迫促进地上生物量的积累，一定浓度的土壤pH值和土壤盐分可以促进琵琶柴群落细根的生长。 Abstract:Reaumuria soongarica is one of the most widely distributed plant species in arid regions of China and has an important role in maintaining the stability of the desert ecosystem. On the basis of field data, including the species composition, number of species, plant height, coverage and abundance, and selected soil properties (electrical conductivity, pH, bulk density and moisture content), the fine root biomass and aboveground biomass of two R. soongarica communities in the Sangong River basin were investigated over the course of the main growing season (from June to October) of 2010. In addition, by calculation of derivative biodiversity indices comprising Pielou's evenness index, Simpson's dominance index, the Shannon-Wiener diversity index, and Sorenson's similarity index, the relationships between fine root biomass, biodiversity and soil properties of the two communities were analyzed. The results showed that the crown area, coverage, abundance, species number, Pielou's evenness index, Simpson's dominance index, Shannon-Wiener diversity index, aboveground biomass, fine root biomass, and the soil electrical conductivity, pH, bulk density and moisture content in the 0-100 cm soil layer of two R. soongarica communities were significantly different. Except for soil bulk density, the values of all soil properties of Community 2 were higher than those of Community 1, and showed similar trends with increment in soil depth. Except for species number and Simpson's dominance index, the other biodiversity indices decreased initially and thereafter increased from June to October, whereas the aboveground biomass and fine root biomass increased initially and thereafter decreased from June to October. Owing to the appearance of a large number of summer rain-dependent herbs in July and August in Community 1, the Shannon-Wiener diversity index and Pielou's evenness index showed sharp reductions over the growing season, whereas Simpson's dominance index showed the opposite trend. Compared with Community 1, Community 2 had higher soil electrical conductivity and soil pH, and few summer rain-dependent herbs, and therefore the Shannon-Wiener diversity index, Pielou's evenness index and Simpson's dominance index changed only moderately. In addition, Sorenson's similarity coefficient was small and the difference between the two communities was significant. Regression analysis showed that soil properties were determinants of the differences in biodiversity and biomass of the two communities. High soil moisture content increased biodiversity, high soil bulk density inhibited fine root growth, and certain soil pH and soil salt contents promoted fine root growth in R. soongarica communities. We concluded that soil salt content and soil pH are the main factors that restrict biodiversity, community structure, and growth of R. soongarica in the Sangong River basin. Differences in microenvironments, especially in soil characteristics, could induce strong differences in two communities with identical dominant species in the same climatic zone. These findings provide a scientific base for management of natural R. soongarica communities and rehabilitation of degraded communities, as well as for improvement of soil salinization in arid regions of China. 参考文献 相似文献 引证文献

The effect of global warming on soil salinity in arid regions

The comparison of modern climatic conditions and soil salinity in subboreal deserts of Middle Asia (Turanian plain) and Central Asia (Gobi deserts) shows that climate has an effect on salinity of hydromorphic soils. From the other hand, the distribution and degree of salinity of automorphic desert soils are predominantly governed by the distribution of salt-bearing rocks inherited from the previous geologic stages and are not related directly to the modern aridity. This fact allows us to state that the global warming will not promote salinization of automorphic soils of arid regions, except for the soils subjected to aeolian salinization. Climate aridification will provoke soil salinization in hydromorphic conditions.

The influence of free convection on soil salinization in arid regions

Evaporation of groundwater in a region with a shallow water table and small natural replenishment causes accumulation of salts near the ground surface. Water in the upper soil layer becomes denser than in the depth. This is a potentially unstable situation which may result in convective currents. When free convection takes place, estimates of the salinity profile, salt precipitation rate, etc., obtained within the framework of a 1-D (vertical) model fail.