Browsing by Author "Dhakal, Sameer"

Now showing 1 - 2 of 2
  • Thumbnail Image
    New water accounting reveals why the Colorado River no longer reaches the sea
    Richter, Brian D.; Lamsal, Gambhir; Marston, Landon T.; Dhakal, Sameer; Sangha, Laljeet Singh; Rushforth, Richard R.; Wei, Dongyang; Ruddell, Benjamin L.; Davis, Kyle Frankel; Hernandez-Cruz, Astrid; Sandoval-Solis, Samuel; Schmidt, John C. (Springer Nature, 2024-03-28)
    Persistent overuse of water supplies from the Colorado River during recent decades has substantially depleted large storage reservoirs and triggered mandatory cutbacks in water use. The river holds critical importance to more than 40 million people and more than two million hectares of cropland. Therefore, a full accounting of where the river’s water goes en route to its delta is necessary. Detailed knowledge of how and where the river’s water is used can aid design of strategies and plans for bringing water use into balance with available supplies. Here we apply authoritative primary data sources and modeled crop and riparian/wetland evapotranspiration estimates to compile a water budget based on average consumptive water use during 2000–2019. Overall water consumption includes both direct human uses in the municipal, commercial, industrial, and agricultural sectors, as well as indirect water losses to reservoir evaporation and water consumed through riparian/wetland evapotranspiration. Irrigated agriculture is responsible for 74% of direct human uses and 52% of overall water consumption. Water consumed for agriculture amounts to three times all other direct uses combined. Cattle feed crops including alfalfa and other grass hays account for 46% of all direct water consumption.
  • Thumbnail Image
    PyCHAMP: A Crop-Hydrological-Agent Modeling Platform for Groundwater Management
    Lin, Chung-Yi; Alegria, Maria Elena Orduna; Dhakal, Sameer; Zipper, Sam; Marston, Landon (Environmental Modelling and Software, 2024-08)
    The Crop-Hydrological-Agent Modeling Platform (PyCHAMP) is a Python-based open-source package designed for modeling agro-hydrological systems. The modular design, incorporating aquifer, crop field, groundwater well, finance, and behavior components, enables users to simulate and analyze the interactions between human and natural systems, considering both environmental and socio-economic factors. This study demonstrates PyCHAMP’s capabilities by simulating the dynamics in the Sheridan 6 Local Enhanced Management Area, a groundwater conservation program in the High Plains Aquifer in Kansas. We highlight how a model, empowered by PyCHAMP, accurately captures human-water dynamics, including groundwater level, water withdrawal, and the fraction of cropland dedicated to each crop. We also show how farmer behavior, and its representation, drives system outcomes more strongly than environmental conditions. The results indicate PyCHAMP’s potential as a useful tool for human-water research and sustainable groundwater management, offering prospects for future integration with detailed sub-models and systematic evaluation of model structural uncertainty.