Modular extremely large-scale MIMO (XL-MIMO) architectures combined with wireless fronthaul provide a scalable alternative to monolithic arrays, but their performance is sensitive to hardware impairments and resource allocation strategies. In this paper, we consider a distributed two-phase processing framework for modular XL-MIMO systems employing amplify-and-forward wireless fronthaul under practical hardware constraints. We jointly model access-side and fronthaul-side distortions and formulate a weighted minimum mean-square error (WMMSE)-based optimization problem that maximizes the uplink sum spectral efficiency (SE) by jointly adjusting UE transmit powers and fronthaul amplification levels. The resulting algorithm alternates between distortion-aware receiver design and convex power-control updates. Numerical results demonstrate that the proposed joint optimization significantly improves spectral efficiency compared to fixed transmission strategies, particularly when the CPU has a moderate number of antennas, while also quantifying the relative impact of access and fronthaul impairments.