基于时空多尺度地表水热行为的大面积平缓地区土壤多要素数字制图

The soil–landscape relationship theory relates difficult-to-measure soil information with some easy-to-obtain soil-forming environmental factors. This makes it possible to infer soil spatial variations from the easy-to-obtain environmental factors. In low relief areas such as plains, however, easily obtained soil forming factors generally do not co-vary with soil conditions over space to the level that they can be used effectively in digital soil mapping. Current studies examined the feasibility of inferring soil texture using soil drying patterns after a rainfall event. But, this approach is only applicable in small areas with the same amount of rainfall and for single specific soil property, i.e. soil texture. The challenge is how to map multiple soil properties over large low-relief areas. To address this issue, this project will investigate easily obtained land surface hydro-thermal behaviors with different temporal-spatial scales, analyze the relations of the behaviors with multiple soil properties and environmental factors, identify the behaviors strongly co-varying with soil properties, construct the environmental covariates which can indicate spatial difference of soil properties, and develop a digital soil mapping approach for large low-relief areas and multiple soil properties. This project can overcome the limitations of current studies, build new digital soil mapping paradigm for low-relief areas, and expand the theory and methodology of digital soil mapping. Moreover, this project can improve the accuracy and efficiency of soil mapping over such areas, and provide more accurate and detailed soil information for digitized soil management, agricultural productions and environmental modeling.

在平原等地形平缓地区，易于观测获取的成土因素信息（地形和植被等）通常与土壤的空间协同程度较低，难以准确地对这类地区进行土壤制图。针对该难题，现有研究探索了利用降雨后土壤水分变化模式推测土壤质地的可行性，但仅适用于小面积降雨同质区和单一特定要素（土壤质地）。如何对大面积平缓地区土壤多要素进行制图仍是一个挑战性问题。本项目拟对易于大面积遥感观测获取的时空多尺度地表水热行为进行研究，分析其与土壤多要素和环境背景之间的驱动和协同关系，识别与土壤要素协同性较强的行为片段，开发能够体现土壤要素空间差异的环境协同变量，建立一套对大面积平缓地区土壤多要素进行数字制图的方法体系。该项目可以突破现有研究工作的思路局限，建立适用于平缓地区的数字土壤制图范式，拓展土壤制图的理论方法；同时，可以提高这类地区制图准确性和效率，满足土壤数字化管理、农业生产和环境模拟对土壤信息的迫切需求。

在平原等地形平缓地区，易于观测获取的成土因素信息（地形和植被等）通常与土壤的空间协同程度较低，难以准确地对这类地区进行土壤制图。针对该难题，已有研究探索了利用降雨后土壤水分变化模式推测土壤质地的可行性，但仅适用于小面积降雨同质区和单一特定要素，如何对大面积平缓地区土壤多要素进行制图仍是一个挑战性问题。为此，本项目主要开展了多尺度（日变化和季节变化等）地表水热行为量化表征及其驱动因素、地表水热行为与土壤理化属性的协同关系、基于地表水热行为的环境协同变量构造方法、大面积平缓地区土壤多要素预测性数字制图方法、地表水热输入强度对土壤预测制图效果的影响等五个方面的研究工作。明确了地表多尺度水热行为与土壤多要素之间的空间协同关系，开发了土壤水热行为定量表征、环境协同变量构造和土壤空间推测的算法，检验了地表水热输入量级对土壤制图效果的影响，建立了一套基于时空多尺度地表水热行为对大面积平缓地区进行土壤多要素数字制图的方法与技术，在三个代表性的大面积平缓地区（湿润区水田景观、半湿润区旱地景观和干旱区荒漠戈壁景观）进行了方法应用验证取得了良好效果。发现基于遥感大面积观测的多尺度地表水热行为信息构造的环境协同变量能够有效地指示土壤多要素（砂粒、粉粒、粘粒、有机碳、PH、容重等）的空间差异，基于这些变量的数字土壤制图可取得较好的制图效果。该项目研究突破了现有工作的思路局限，完善了之前平缓地区土壤制图方法，在很大程度上克服了这类地区土壤预测制图的困难，提高了这类地区土壤推测制图的准确性和效率，形成了适用于平缓地区数字土壤制图范式，拓展现有的数字土壤制图理论与方法，该研究成果有助于满足土壤数字化管理、农业生产和环境模拟对高精度土壤信息的迫切需求。

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