{"title":"Sensitivity of Groundwater Recharge Assessment to Input Data in Arid Areas","authors":"S. Ajjur, Emanuele Di Lorenzo","doi":"10.3390/hydrology11020028","DOIUrl":null,"url":null,"abstract":"Natural groundwater recharge (GR) assessment depends on several hydrogeological and climatic inputs, where uncertainty is inevitable. Assessing how inputs’ uncertainty affects GR estimation is important; however, it remains unclear in arid areas. This study assesses inputs’ uncertainty by examining the changes in GR simulations resulting from modifications in climatic, land use, and soil inputs. A physical-based hydrological model was built to estimate GR from 18 different GR scenarios across Qatar. Scenarios S1–S7 were created from different climatic inputs but identical land use and soil maps. Scenarios S8–S14 were created from different land use maps (analyzed from historical Landsat satellite images) but similar climatic and soil inputs. In S15–S18, the soil parameters were changed while the climatic and land use maps were kept the same. The results show that climatic inputs are key factors controlling the GR in arid areas, followed by land use inputs and soil classification. A strong correlation was observed between the GR values and precipitation, while moderate (non-significant) correlations were observed between the GR values and potential evapotranspiration and wind speed. Soil changes affected the GR simulations but inconsiderably compared with climatic and land use inputs. Since GR estimation is fundamental but uncertain in arid areas, the study findings contribute to narrowing the uncertainty in GR estimation.","PeriodicalId":508746,"journal":{"name":"Hydrology","volume":"882 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/hydrology11020028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Natural groundwater recharge (GR) assessment depends on several hydrogeological and climatic inputs, where uncertainty is inevitable. Assessing how inputs’ uncertainty affects GR estimation is important; however, it remains unclear in arid areas. This study assesses inputs’ uncertainty by examining the changes in GR simulations resulting from modifications in climatic, land use, and soil inputs. A physical-based hydrological model was built to estimate GR from 18 different GR scenarios across Qatar. Scenarios S1–S7 were created from different climatic inputs but identical land use and soil maps. Scenarios S8–S14 were created from different land use maps (analyzed from historical Landsat satellite images) but similar climatic and soil inputs. In S15–S18, the soil parameters were changed while the climatic and land use maps were kept the same. The results show that climatic inputs are key factors controlling the GR in arid areas, followed by land use inputs and soil classification. A strong correlation was observed between the GR values and precipitation, while moderate (non-significant) correlations were observed between the GR values and potential evapotranspiration and wind speed. Soil changes affected the GR simulations but inconsiderably compared with climatic and land use inputs. Since GR estimation is fundamental but uncertain in arid areas, the study findings contribute to narrowing the uncertainty in GR estimation.
天然地下水补给(GR)评估取决于若干水文地质和气候输入,其中不确定性不可避免。评估输入的不确定性如何影响地下水补给估算非常重要,但在干旱地区仍不明确。本研究通过考察气候、土地利用和土壤输入的变化对 GR 模拟的影响来评估输入的不确定性。建立了一个基于物理的水文模型,以估算卡塔尔 18 种不同的 GR 情景下的 GR 值。情景 S1-S7 根据不同的气候输入创建,但土地利用和土壤地图相同。情景 S8-S14 是根据不同的土地利用图(通过历史大地遥感卫星图像分析)创建的,但气候和土壤输入相似。在 S15-S18 中,土壤参数发生了变化,但气候和土地利用图保持不变。结果表明,气候输入是控制干旱地区 GR 的关键因素,其次是土地利用输入和土壤分类。GR 值与降水量之间存在很强的相关性,而 GR 值与潜在蒸散量和风速之间存在中等程度(不显著)的相关性。土壤变化对 GR 模拟产生了影响,但与气候和土地利用输入相比影响不大。由于干旱地区的全球平均降水量估算非常重要,但也存在不确定性,因此研究结果有助于缩小全球平均降水量估算的不确定性。