Chhachhar Rabia, Abbasi Habibullah
Centre for Environmental Sciences, Faculty of Natural Sciences, University of Sindh, Jamshoro, Pakistan.
Sci Prog. 2024 Apr-Jun;107(2):368504241251655. doi: 10.1177/00368504241251655.
The water availability concerns have been increasing due to significant impacts of land use land cover change, and climate variability. In terms of developing countries, it is one of the biggest challenges to overcome and manage sustainability in the present and future. This study aims to evaluate the change in hydrological components and simulation of sediment yield and water yield on the large-scale basin of Kotri barrage with a change in runoff due to a change in land use land cover. This study has been done on the watershed as well as the sub-watershed level to have an accurate estimation and simulation by finding the response of hydrological components toward its natural and human-induced factors using the Soil and Water Assessment tool with high-resolution geospatial-temporal inputs over the Kotri catchment. The sediment and water yield were quantified using 42 years of simulation (1981-2022) on the sub-basin level, projected to land use land cover 1990, 2000, 2010, and 2022. The increase in deforestation, agriculture, and settlement areas resulted increase in sediment load in the catchment. The sub-basins 14, 11, 12, and 13, with a high elevation and slope and with less vegetation showed higher sediment load and water yield than the sub-basins with gentle slope and with high natural vegetation cover. The sub-basins 10, 4, and 1 showed high water yield availability compared to basins 2, 3, 5, 6, 7, 8, 9. This may be the result of vegetation differences. However, contained less sediment load than basins 14, 11, 12, and 13. The main objective was to quantify the significant changes affecting catchment and sub-catchment areas, to have a better understanding of the management plan regarding land use land cover. The simulated data was further projected to prediction using machine algorithms (autoregressive integrated moving average) model for precipitation prediction, and (seasonal autoregressive integrated moving average with exogenous factors) model to predict the sediment yield and water yield in the catchment to 2060.
由于土地利用土地覆盖变化和气候变异性的重大影响，水资源可用性问题日益突出。对于发展中国家而言，这是当前和未来在克服和管理可持续性方面面临的最大挑战之一。本研究旨在评估科特里拦河坝大型流域水文要素的变化，以及土地利用土地覆盖变化导致径流变化时沉积物产量和产水量的模拟。本研究在流域以及子流域层面进行，通过使用土壤和水评估工具，并结合科特里集水区高分辨率的地理空间-时间输入，找到水文要素对其自然和人为因素的响应，从而进行准确的估算和模拟。在子流域层面，利用42年的模拟数据（1981 - 2022年）对沉积物和产水量进行了量化，并将其投影到1990年、2000年、2010年和2022年的土地利用土地覆盖情况。森林砍伐、农业和定居面积的增加导致集水区沉积物负荷增加。海拔高、坡度大且植被较少的第14、11、12和13个子流域，其沉积物负荷和产水量高于坡度平缓且自然植被覆盖率高的子流域。与第2、3、5、6、7、8、9号流域相比，第10、4和1号子流域的产水量较高。这可能是植被差异的结果。然而，其沉积物负荷比第14、11、12和13号流域少。主要目的是量化影响集水区和子集水区的重大变化，以便更好地理解关于土地利用土地覆盖的管理计划。利用机器学习算法（自回归积分滑动平均）模型对降水进行预测，并利用（带有外生因素的季节性自回归积分滑动平均）模型对集水区到2060年的沉积物产量和产水量进行预测，进一步对模拟数据进行预测。
