{"title":"比较微型盘式入渗仪、BEST 法和土壤岩芯对砂质壤土导水率的估算值","authors":"Mariachiara Fusco, Vincenzo Alagna, Dario Autovino, Gaetano Caltabellotta, Massimo Iovino, Girolamo Vaccaro, Vincenzo Bagarello","doi":"10.1016/j.still.2024.106263","DOIUrl":null,"url":null,"abstract":"<div><p>Saturated, <em>K</em><sub><em>s</em></sub>, and near-saturated, <em>K</em>, soil hydraulic conductivity control many hydrological processes but they are difficult to measure. Comparing methods to determine <em>K</em><sub><em>s</em></sub> and <em>K</em> is a means to establish how and why these soil hydrodynamic properties vary with the applied method. A comparison was established between the <em>K</em><sub><em>s</em></sub> and <em>K</em> values of a sandy-loam soil obtained, in the field, with the BEST (Beerkan Estimation of Soil Transfer parameters) method of soil hydraulic characterization and an unconfined MDI (mini-disk infiltrometer) experiment and, in the laboratory, with a confined MDI experiment and the CHP (constant-head permeameter) method. Using for the BEST calculations the soil porosity instead of the saturated soil water content yielded 1.4–1.1 times higher estimates of <em>K</em><sub><em>s</em></sub> and <em>K</em>, depending on the pressure head, and differences decreased in more unsaturated soil conditions. The confined MDI experiment yielded 22 % - 77 % higher <em>K</em> values than the unconfined MDI experiment, depending on the established pressure head, <em>h</em><sub>0</sub>, and differences were not significant for <em>h</em><sub>0</sub> = −1 cm. In the close to saturation region, the soil hydraulic conductivity function predicted with BEST did not generally agree well with the <em>K</em><sub><em>s</em></sub> and <em>K</em> values obtained in the laboratory by a direct application of the Darcy’s law. In particular, BEST yielded a 5.6 times smaller <em>K</em><sub><em>s</em></sub> value than the CHP method and up to an 8.1 times higher <em>K</em> value than the MDI. Overall, i) the two application methods of the MDI yielded relatively similar results, especially close to saturation, and ii) there was not a satisfactory agreement between the field (BEST) and the laboratory (MDI plus CHP) determination of soil hydraulic conductivity close to saturation, unless a comparison was made with the same soil water content. The detected differences were probably attributable to soil spatial variability, overestimation of <em>K</em><sub><em>s</em></sub> in the laboratory due to preferential flow phenomena, underestimation of <em>K</em><sub><em>s</em></sub> in the field due to air entrapment in the soil and infiltration surface disturbance, inability of BEST to describe the actual soil hydraulic conductivity function at the sampled field site. Testing BEST predictions of <em>K</em><sub><em>s</em></sub> and <em>K</em> in other soils appears advisable and combining the MDI and CHP methods appears a rather simple means to make these checks. These additional investigations could improve interpretation of the differences between methods, which is an important step for properly selecting a method yielding <em>K</em><sub><em>s</em></sub> and <em>K</em> data appropriate for an intended use.</p></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"244 ","pages":"Article 106263"},"PeriodicalIF":6.1000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparing mini-disk infiltrometer, BEST method and soil core estimates of hydraulic conductivity of a sandy-loam soil\",\"authors\":\"Mariachiara Fusco, Vincenzo Alagna, Dario Autovino, Gaetano Caltabellotta, Massimo Iovino, Girolamo Vaccaro, Vincenzo Bagarello\",\"doi\":\"10.1016/j.still.2024.106263\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Saturated, <em>K</em><sub><em>s</em></sub>, and near-saturated, <em>K</em>, soil hydraulic conductivity control many hydrological processes but they are difficult to measure. Comparing methods to determine <em>K</em><sub><em>s</em></sub> and <em>K</em> is a means to establish how and why these soil hydrodynamic properties vary with the applied method. A comparison was established between the <em>K</em><sub><em>s</em></sub> and <em>K</em> values of a sandy-loam soil obtained, in the field, with the BEST (Beerkan Estimation of Soil Transfer parameters) method of soil hydraulic characterization and an unconfined MDI (mini-disk infiltrometer) experiment and, in the laboratory, with a confined MDI experiment and the CHP (constant-head permeameter) method. Using for the BEST calculations the soil porosity instead of the saturated soil water content yielded 1.4–1.1 times higher estimates of <em>K</em><sub><em>s</em></sub> and <em>K</em>, depending on the pressure head, and differences decreased in more unsaturated soil conditions. The confined MDI experiment yielded 22 % - 77 % higher <em>K</em> values than the unconfined MDI experiment, depending on the established pressure head, <em>h</em><sub>0</sub>, and differences were not significant for <em>h</em><sub>0</sub> = −1 cm. In the close to saturation region, the soil hydraulic conductivity function predicted with BEST did not generally agree well with the <em>K</em><sub><em>s</em></sub> and <em>K</em> values obtained in the laboratory by a direct application of the Darcy’s law. In particular, BEST yielded a 5.6 times smaller <em>K</em><sub><em>s</em></sub> value than the CHP method and up to an 8.1 times higher <em>K</em> value than the MDI. Overall, i) the two application methods of the MDI yielded relatively similar results, especially close to saturation, and ii) there was not a satisfactory agreement between the field (BEST) and the laboratory (MDI plus CHP) determination of soil hydraulic conductivity close to saturation, unless a comparison was made with the same soil water content. The detected differences were probably attributable to soil spatial variability, overestimation of <em>K</em><sub><em>s</em></sub> in the laboratory due to preferential flow phenomena, underestimation of <em>K</em><sub><em>s</em></sub> in the field due to air entrapment in the soil and infiltration surface disturbance, inability of BEST to describe the actual soil hydraulic conductivity function at the sampled field site. Testing BEST predictions of <em>K</em><sub><em>s</em></sub> and <em>K</em> in other soils appears advisable and combining the MDI and CHP methods appears a rather simple means to make these checks. These additional investigations could improve interpretation of the differences between methods, which is an important step for properly selecting a method yielding <em>K</em><sub><em>s</em></sub> and <em>K</em> data appropriate for an intended use.</p></div>\",\"PeriodicalId\":49503,\"journal\":{\"name\":\"Soil & Tillage Research\",\"volume\":\"244 \",\"pages\":\"Article 106263\"},\"PeriodicalIF\":6.1000,\"publicationDate\":\"2024-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Soil & Tillage Research\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167198724002642\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOIL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soil & Tillage Research","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167198724002642","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOIL SCIENCE","Score":null,"Total":0}
引用次数: 0
摘要
饱和土壤导流系数 Ks 和近饱和土壤导流系数 K 控制着许多水文过程,但它们很难测量。比较测定 Ks 和 K 的方法是确定这些土壤水动力特性如何以及为何随所用方法而变化的一种手段。我们对一种砂质壤土的 Ks 和 K 值进行了比较:在野外,采用 BEST(贝肯土壤传输参数估计)方法进行土壤水力特征描述和非封闭式 MDI(微型盘式渗透仪)实验;在实验室,采用封闭式 MDI 实验和 CHP(恒定水头渗透仪)方法。在 BEST 计算中,使用土壤孔隙度而不是饱和土壤含水量估算出的 Ks 和 K 值要高出 1.4-1.1 倍,具体取决于压力水头,而在更非饱和的土壤条件下,差异会减小。密闭 MDI 试验得出的 K 值比非密闭 MDI 试验高出 22% - 77%,具体取决于既定的压力水头 h0,在 h0 = -1 厘米时差异不明显。在接近饱和区域,用 BEST 预测的土壤导水函数与实验室直接应用达西定律得到的 Ks 和 K 值通常不太一致。特别是,BEST 得出的 Ks 值比 CHP 方法小 5.6 倍,比 MDI 得出的 K 值高 8.1 倍。总体而言,i) MDI 的两种施用方法得出的结果相对相似,尤其是接近饱和状态时;ii) 除非在土壤含水量相同的情况下进行比较,否则现场(BEST)和实验室(MDI 加 CHP)测定的接近饱和状态的土壤导水性之间的一致性并不令人满意。检测到的差异可能是由于土壤空间变异、优先流现象导致实验室高估了 Ks、土壤中的空气截留和渗透表面扰动导致实地低估了 Ks,以及 BEST 无法描述取样实地的实际土壤导水函数。在其他土壤中测试 BEST 对 Ks 和 K 的预测似乎是可取的,而结合 MDI 和 CHP 方法似乎是进行这些检查的一个相当简单的方法。这些额外的调查可以改进对不同方法之间差异的解释,而这是正确选择一种能产生适合预期用途的 Ks 和 K 数据的方法的重要步骤。
Comparing mini-disk infiltrometer, BEST method and soil core estimates of hydraulic conductivity of a sandy-loam soil
Saturated, Ks, and near-saturated, K, soil hydraulic conductivity control many hydrological processes but they are difficult to measure. Comparing methods to determine Ks and K is a means to establish how and why these soil hydrodynamic properties vary with the applied method. A comparison was established between the Ks and K values of a sandy-loam soil obtained, in the field, with the BEST (Beerkan Estimation of Soil Transfer parameters) method of soil hydraulic characterization and an unconfined MDI (mini-disk infiltrometer) experiment and, in the laboratory, with a confined MDI experiment and the CHP (constant-head permeameter) method. Using for the BEST calculations the soil porosity instead of the saturated soil water content yielded 1.4–1.1 times higher estimates of Ks and K, depending on the pressure head, and differences decreased in more unsaturated soil conditions. The confined MDI experiment yielded 22 % - 77 % higher K values than the unconfined MDI experiment, depending on the established pressure head, h0, and differences were not significant for h0 = −1 cm. In the close to saturation region, the soil hydraulic conductivity function predicted with BEST did not generally agree well with the Ks and K values obtained in the laboratory by a direct application of the Darcy’s law. In particular, BEST yielded a 5.6 times smaller Ks value than the CHP method and up to an 8.1 times higher K value than the MDI. Overall, i) the two application methods of the MDI yielded relatively similar results, especially close to saturation, and ii) there was not a satisfactory agreement between the field (BEST) and the laboratory (MDI plus CHP) determination of soil hydraulic conductivity close to saturation, unless a comparison was made with the same soil water content. The detected differences were probably attributable to soil spatial variability, overestimation of Ks in the laboratory due to preferential flow phenomena, underestimation of Ks in the field due to air entrapment in the soil and infiltration surface disturbance, inability of BEST to describe the actual soil hydraulic conductivity function at the sampled field site. Testing BEST predictions of Ks and K in other soils appears advisable and combining the MDI and CHP methods appears a rather simple means to make these checks. These additional investigations could improve interpretation of the differences between methods, which is an important step for properly selecting a method yielding Ks and K data appropriate for an intended use.
期刊介绍:
Soil & Tillage Research examines the physical, chemical and biological changes in the soil caused by tillage and field traffic. Manuscripts will be considered on aspects of soil science, physics, technology, mechanization and applied engineering for a sustainable balance among productivity, environmental quality and profitability. The following are examples of suitable topics within the scope of the journal of Soil and Tillage Research:
The agricultural and biosystems engineering associated with tillage (including no-tillage, reduced-tillage and direct drilling), irrigation and drainage, crops and crop rotations, fertilization, rehabilitation of mine spoils and processes used to modify soils. Soil change effects on establishment and yield of crops, growth of plants and roots, structure and erosion of soil, cycling of carbon and nutrients, greenhouse gas emissions, leaching, runoff and other processes that affect environmental quality. Characterization or modeling of tillage and field traffic responses, soil, climate, or topographic effects, soil deformation processes, tillage tools, traction devices, energy requirements, economics, surface and subsurface water quality effects, tillage effects on weed, pest and disease control, and their interactions.