An integrated scenario-based approach for evaluating water yield responses to land use and climate change

Abstract

The assessment of water yield (WY) as a key ecosystem service (ES) is crucial, as it is strongly influenced by anthropogenic activities. This study focuses on the Tajan Watershed (Mazandaran Province), Iran, a region affected by land use/land cover (LULC) and climate change. The CA-Markov model was used to predict LULC for 2040 based on three scenarios: i) Natural Development (ND); ii) Ecological Conservation (EC); and iii) Anthropogenic Space Restrictions (ASR). Climate change assessments for 2024–2040 were projected using the MRI-ESM2-0 model under the SSP2-4.5 scenario. The InVEST model was implemented to calculate WY based on the studied scenarios. The prepared LULC maps for 2000–2024 using Landsat family images showed that forest and barren areal extent have decreased; in contrast, cropland, construction land, and water bodies have increased. A similar trend was also found for 2040 when using the ND scenario. Regarding the EC scenario, the highest variation was observed for cropland (13.6 %) and forest (11.5 %). The third examined scenario demonstrated that cropland and construction land areas have declined by 6.5 % and 1.5 %, respectively. These changes directly impact WY. For instance, it has decreased by 6.67 million cubic meters (MCM) over the last 24 years. The results imply that the highest WY (in MCM) was for the scenarios of ND (54.99), followed by EC (53.35) and ASR (36.19). This research highlights the novel use of remote sensing in ecological modeling, particularly in data-limited areas. It also enhances our understanding of WY dynamics under the combined impacts of LULC and climate change.