Understanding the environmental pathways of Cryptosporidium is essential for effective management of human and animal cryptosporidiosis. In this paper we aim to quantify livestock Cryptosporidium spp. loads to land on a global scale using spatially explicit process-based modeling, and to explore the effect of manure storage and treatment on oocyst loads using scenario analysis. Our model GloWPa-Crypto L1 calculates a total global Cryptosporidium spp. load from livestock manure of 3.2 × 1023 oocysts per year. Cattle, especially calves, are the largest contributors, followed by chickens and pigs. Spatial differences are linked to animal spatial distributions. North America, Europe, and Oceania together account for nearly a quarter of the total oocyst load, meaning that the developing world accounts for the largest share. GloWPa-Crypto L1 is most sensitive to oocyst excretion rates, due to large variation reported in literature. We compared the current situation to four alternative management scenarios. We find that although manure storage halves oocyst loads, manure treatment, especially of cattle manure and particularly at elevated temperatures, has a larger load reduction potential than manure storage (up to 4.6 log units). Regions with high reduction potential include India, Bangladesh, western Europe, China, several countries in Africa, and New Zealand.