Field-based investigations of land use/cover changes are time-consuming and challenging for large areas, where short- and long-term changes in climatic and hydrologic variables affect ecosystem services. Thus, there is a substantial demand to boost the new modelling framework and employ remote sensing capabilities to quantify hydro-climatic impacts on land dynamics. In this study, a conceptual framework has used to assess the climatic land greening, climatic land degradation, nonclimatic (hydrological) land greening, and nonclimatic (anthropogenic) land degradation responses with hydro-climatic variables under dry and wet spells' effect in the Betwa River basin (BRB) of central India. Remotely sensed moderate-resolution imaging spectro-radiometer (MODIS) (normalized difference vegetation index [NDVI] and land cover) time-series datasets had been used to quantify spatiotemporal changes in major land use/cover classes. The standardized coefficients for rainfall (β = 0.62) and relative humidity (β = 0.32) showed their high relative importance in the relationship analysis performed using multiple linear regression (MLR). The result indicates that dominant agricultural cropland has been significantly impacted by changes in maximum and diurnal temperature, which affirm degradation, and positively responded by changes in rainfall, minimum temperature, and aridity index, which demonstrate greening wet period. Spatial analysis showed that land degradation affecting ecosystem services had been variedly distributed from the upper to lower basin due to more climatic impacts than anthropogenic disturbances. Thus, the developed conceptual framework can be adopted to discover dynamic land consequences and understand their responses for sustaining ecosystem services in the dominant agricultural region.

中文翻译：

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使用概念框架评估土地退化和绿化对水文气候变量变化的响应：印度中部的案例研究

土地利用/覆盖变化的实地调查对于大面积地区来说既耗时又具有挑战性，因为气候和水文变量的短期和长期变化会影响生态系统服务。因此，迫切需要推进新的建模框架并利用遥感能力来量化水文气候对土地动态的影响。在这项研究中，一个概念框架用于评估气候土地绿化、气候土地退化、非气候（水文）土地绿化和非气候（人为）土地退化响应，以及在干湿期影响下 Betwa 的水文气候变量。印度中部河流域（BRB）。遥感中分辨率成像光谱辐射计 (MODIS)（归一化差异植被指数 [NDVI] 和土地覆盖）时间序列数据集已被用于量化主要土地利用/覆盖类别的时空变化。降雨的标准化系数（β  = 0.62) 和相对湿度 ( β = 0.32) 表明它们在使用多元线性回归 (MLR) 进行的关系分析中具有较高的相对重要性。结果表明，优势农田受到最高和昼夜温度变化的显着影响，表明退化，并受到降雨、最低温度和干旱指数变化的积极响应，表明绿湿期。空间分析表明，由于气候影响多于人为干扰，影响生态系统服务的土地退化从上流域到下流域分布不同。因此，可以采用已开发的概念框架来发现动态土地后果并了解它们对维持优势农业区域生态系统服务的响应。