Farm dams may exert various pressures on the flow network depending on the position and scale, which may influence the magnitude, timing, and duration of the flow in the basin. Considering the cumulative effects of farm dams is important for understanding their spatial impacts on the rainfall-runoff process. However, a few studies have been able to reckon the temporal and spatial variation in the flow. In this study, we developed an integrated approach based on remote sensing and hydrologic–hydrodynamic modeling to simulate the rainfall-runoff process in a farm dam-dominated basin. Compared with the classical Xinanjiang model (XAJ), the developed coupled hydrological–hydrodynamic model (coupled-XAJ) shows improved performance in the simulation of the no-linear confluence process in terms of flood flow and peak appearance time. It demonstrates that water retention of multiple farm dams is eminent and that the developed model is effective and feasible in farm dam-dominated basins. Furthermore, the integrated approach enables to control and utilize the rain and flood resources with the safety of arm dams guaranteed. This study provides an innovative method for the scientific management of water resources under the influence of human activities and environmental changes.

Land systems in drylands have been experiencing increasing conflicts among different land functions due to ecological vulnerability and growing demands. The improvement of one function is often at the cost of other functions, which causes trade-offs of functions. Understanding land multifunctionality and its trade-offs are prerequisites to alleviate land use conflicts and achieve land sustainability. But research often cannot well address the fuzziness and uncertainty within assessments, and neglect the nonlinear feature when quantifying the trade-offs. Taking the Heihe River Basin (HRB), a typical arid ecologically vulnerable area in China, as the study area, we applied the set pair analysis (SPA) to develop a novel framework for assessing land multifunctionality at a fine scale from the production-living-ecological angle. We then utilized the constraint line fitted with segmented quantile regression to identify the trade-offs among land functions and understand the bidirectional interaction between land systems. The results showed that the overall land multifunctionality in HRB showed an upward trend during 2000-2015, and especially the production and living functions had a larger magnitude. We used the coupling coordination degree to comprehensively indicate the interaction and found that the degree was high in the south and low in the north, which was mainly controlled by ecological function. The effects of different drivers on land functions showed nonlinear characteristics, and thresholds existed for some influencing factors. Our research provides reliable and detailed information to coordinated the development of land systems, which is helpful for sustainable land use and territorial spatial planning.