diff --git a/modules/data.land/R/look_up_fertilizer_components.R b/modules/data.land/R/look_up_fertilizer_components.R
index 0f07ac47d21..ed6a7818d50 100644
--- a/modules/data.land/R/look_up_fertilizer_components.R
+++ b/modules/data.land/R/look_up_fertilizer_components.R
@@ -104,7 +104,7 @@ look_up_fertilizer_components <- function(
       )
       
       res <- fertilizer_info |>
-        dplyr::select(.data$name, .data$NO3_N, .data$NH4_N, .data$N_org, .data$C_org) |>
+        dplyr::select("name", "NO3_N", "NH4_N", "N_org", "C_org") |>
         dplyr::rename(type = .data$name) |>
         as.list()
     return(res)
diff --git a/modules/data.land/inst/events_schema_v0.1.0.json b/modules/data.land/inst/events_schema_v0.1.0.json
new file mode 100644
index 00000000000..21a853f8bc3
--- /dev/null
+++ b/modules/data.land/inst/events_schema_v0.1.0.json
@@ -0,0 +1,73 @@
+{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "$id": "https://pecanproject.org/schema/events-mvp-0-1-0.json",
+  "type": "object",
+  "required": ["pecan_events_version", "site_id", "events"],
+  "properties": {
+    "pecan_events_version": { "type": "string", "const": "0.1.0" },
+    "site_id": { "type": "string", "minLength": 1 },
+    "ensemble_id": { "type": ["string", "null"], "minLength": 1 },
+    "geometry_uri": { "type": ["string", "null"], "format": "uri" },
+    "provenance": { "type": "object", "additionalProperties": true },
+    "events": {
+      "type": "array",
+      "items": {
+        "type": "object",
+        "required": ["event_type", "date"],
+        "properties": {
+          "event_type": {
+            "type": "string",
+            "enum": ["planting", "harvest", "irrigation", "fertilization", "tillage"]
+          },
+          "date": { "type": "string", "pattern": "^\\d{4}-\\d{2}-\\d{2}$" },
+          "fraction_area": { "type": "number", "minimum": 0, "maximum": 1, "default": 1.0 },
+          "source": { "type": "string" },
+
+          "leaf_c_kg_m2": { "type": "number", "minimum": 0 },
+          "wood_c_kg_m2": { "type": "number", "minimum": 0 },
+          "fine_root_c_kg_m2": { "type": "number", "minimum": 0 },
+          "coarse_root_c_kg_m2": { "type": "number", "minimum": 0 },
+          "cultivar": { "type": "string" },
+          "crop_code": { "type": "string" },
+          "crop_display": { "type": "string" },
+
+          "frac_above_removed_0to1": { "type": "number", "minimum": 0, "maximum": 1 },
+          "frac_below_removed_0to1": { "type": "number", "minimum": 0, "maximum": 1 },
+          "frac_above_to_litter_0to1": { "type": "number", "minimum": 0, "maximum": 1 },
+          "frac_below_to_litter_0to1": { "type": "number", "minimum": 0, "maximum": 1 },
+
+          "amount_mm": { "type": "number", "minimum": 0 },
+          "method": { "type": "string", "enum": ["soil", "canopy", "flood"] },
+          "immed_evap_frac_0to1": { "type": "number", "minimum": 0, "maximum": 1 },
+
+          "org_c_kg_m2": { "type": "number", "minimum": 0 },
+          "org_n_kg_m2": { "type": "number", "minimum": 0 },
+          "nh4_n_kg_m2": { "type": "number", "minimum": 0 },
+          "no3_n_kg_m2": { "type": "number", "minimum": 0 },
+
+          "tillage_eff_0to1": { "type": "number", "minimum": 0 },
+          "intensity_category": { "type": "string" },
+          "depth_m": { "type": "number", "minimum": 0 }
+        },
+        "allOf": [
+          { "if": { "properties": { "event_type": { "const": "planting" } } },
+            "then": { "required": ["leaf_c_kg_m2"] } },
+          { "if": { "properties": { "event_type": { "const": "harvest" } } },
+            "then": { "required": ["frac_above_removed_0to1"] } },
+          { "if": { "properties": { "event_type": { "const": "irrigation" } } },
+            "then": { "required": ["amount_mm", "method"] } },
+          { "if": { "properties": { "event_type": { "const": "fertilization" } } },
+            "then": { "anyOf": [
+              { "required": ["org_c_kg_m2"] },
+              { "required": ["nh4_n_kg_m2"] },
+              { "required": ["no3_n_kg_m2"] }
+            ] } },
+          { "if": { "properties": { "event_type": { "const": "tillage" } } },
+            "then": { "required": ["tillage_eff_0to1"] } }
+        ],
+        "additionalProperties": true
+      }
+    }
+  },
+  "additionalProperties": false
+}
diff --git a/modules/data.land/inst/generate_events.R b/modules/data.land/inst/generate_events.R
new file mode 100755
index 00000000000..f44f148821f
--- /dev/null
+++ b/modules/data.land/inst/generate_events.R
@@ -0,0 +1,258 @@
+#!/usr/bin/env Rscript
+
+# --- Profiling Start ---
+# Rprof("profiling.out")
+# --- End Profiling Start ---
+
+# Minimal MVP: build mvp_events.json from ca_field_attributes.csv
+# - Input:  data/ca_field_attributes.csv (columns: site_id, year, pft, ...)
+# - Output: data/mvp_events.json following data/pecan_events_schema_v0.1.0.json
+# - Events (minimal):
+#     * planting:  annual crops -> every site-year; woody perennials -> first observed year only
+#     * harvest:   all site-years
+#   Each event includes only the schema-required fields per event_type.
+
+# --- Config ---
+data_dir <- "/projectnb2/dietzelab/ccmmf/data"
+field_attr_csv <- file.path(data_dir, "ca_field_attributes.csv")
+sample_output_json <- file.path(data_dir, "events/mvp_events.json")
+output_json <- file.path(data_dir, "events/events.json")
+
+# if TRUE, only generate for design points
+# TODO: generate full set for all sites to use in site selection and downscaling
+DESIGN_POINTS <- TRUE
+
+PRODUCTION <- FALSE # set TRUE for all sites, not needed if DESIGN_POINTS is TRUE
+if (PRODUCTION) {
+  stop("This could be very slow; consider profiling and writing to db or arrow etc")
+}
+set.seed(123)
+
+ca_field_attributes <- vroom::vroom(
+field_attr_csv,
+  show_col_types = FALSE
+)
+
+if (DESIGN_POINTS) {
+  # design_points <- readr::read_csv("https://raw.githubusercontent.com/ccmmf/workflows/refs/heads/main/data/design_points.csv")
+  # d <- update_design_point_site_ids(design_points, ca_field_attributes)
+  # readr::write_csv(d, file.path(data_dir, "design_points.csv"))
+  # readr::write_csv(d, "~/downscaling/data/design_points.csv")
+  # design_points <- readr::read_csv(file.path(data_dir, "design_points.csv"))
+  # use the one under version control
+  design_points <- readr::read_csv("~/downscaling/data/design_points.csv")
+  ca_field_attributes <- ca_field_attributes |>
+    dplyr::filter(site_id %in% design_points$site_id)
+} else if (!PRODUCTION) {
+  ca_field_attributes <- ca_field_attributes |>
+    dplyr::slice_sample(n = 1000)
+}
+
+ca_fields <- ca_field_attributes |>
+  dplyr::select(site_id, pft, crop) |>
+  dplyr::distinct() |>
+  tidyr::crossing(year = 2016:2024) |>
+  dplyr::group_by(site_id) |>
+  dplyr::mutate(first_year = min(year)) |>
+  dplyr::ungroup()
+
+# Planting (annuals)
+planting_annual <- ca_fields |>
+  dplyr::filter(pft == "annual crop") |>
+  dplyr::transmute(
+    event_type = "planting",
+    date = paste0(year, "-03-15"),
+    site_id = site_id,
+    # required for planting
+    leaf_c_kg_m2 = 0.05,
+    crop = crop
+  )
+
+# Planting (woody): first year
+planting_woody <- ca_fields |>
+  dplyr::filter(pft == "woody perennial crop") |>
+  dplyr::filter(year == first_year) |>
+  dplyr::transmute(
+    event_type = "planting",
+    date = paste0(year, "-03-15"),
+    site_id = site_id,
+    leaf_c_kg_m2 = 0.2,
+    crop = crop
+  )
+
+# Fertilization
+fertilization <- ca_fields |>
+  dplyr::transmute(
+    event_type = "fertilization",
+    date = paste0(year, "-02-11"),
+    site_id = site_id,
+    org_n_kg_m2 = 0.0,
+    org_c_kg_m2 = 0.0,
+    nh4_n_kg_m2 = 0.02,
+    no3_n_kg_m2 = 0.03
+  )
+
+# Organic Matter Addition
+organic_matter_addition <- ca_fields |>
+  dplyr::transmute(
+    event_type = "fertilization",
+    date = paste0(year, "-03-11"),
+    site_id = site_id,
+    org_n_kg_m2 = 0.05,
+    org_c_kg_m2 = 0.5,
+    nh4_n_kg_m2 = 0.0,
+    no3_n_kg_m2 = 0.0
+  )
+
+# Harvest
+harvest <- ca_fields |>
+  dplyr::transmute(
+    event_type = "harvest",
+    date = paste0(year, "-10-15"),
+    site_id = site_id,
+    frac_above_removed_0to1 = 0.10,
+    frac_below_removed_0to1 = 0.0,
+    frac_above_to_litter_0to1 = 0.0,
+    frac_below_to_litter_0to1 = 0.0,
+    crop = crop
+  )
+
+# Pruning (woody)
+pruning <- ca_fields |>
+  dplyr::filter(pft == "woody perennial crop") |>
+  dplyr::mutate(offset = year - first_year) |>
+  dplyr::filter(offset %% 4 == 1) |>
+  dplyr::transmute(
+    event_type                  = "harvest",
+    date                        = paste0(year, "-12-15"),
+    site_id                     = site_id,
+    frac_above_removed_0to1     = 0.30,
+    frac_below_removed_0to1     = 0.0,
+    frac_above_to_litter_0to1   = 0.0,
+    frac_below_to_litter_0to1   = 0.0,
+    crop                        = crop
+  )
+
+# Tillage
+tillage <- ca_fields |>
+  dplyr::filter(pft == "annual crop") |>
+  tidyr::crossing(till_suffix = c("-03-01", "-11-01")) |>
+  dplyr::transmute(
+    event_type         = "tillage",
+    date               = paste0(year, till_suffix),
+    site_id            = site_id,
+    tillage_eff_0to1   = 0.10
+  )
+
+# Irrigation (both pfts): 3 per month for all months
+# TODO: Should annual crops skip irrigation during fallow season?
+months <- sprintf("%02d", 1:12)
+days <- c("05", "15", "25")
+
+irrigation <- ca_fields |>
+  tidyr::crossing(month = months, day = days) |>
+  dplyr::transmute(
+    event_type = "irrigation",
+    date       = paste0(year, "-", month, "-", day),
+    site_id    = site_id,
+    amount_mm  = 40,
+    method     = "soil"
+  )
+
+# Combine and order by site/date
+events_all <- dplyr::bind_rows(
+  planting_annual, planting_woody,
+  harvest, pruning,
+  tillage, irrigation,
+  fertilization, organic_matter_addition
+) |>
+  dplyr::arrange(site_id, date)
+
+# --- Build site objects per schema ------------------------------------------
+# Helper: drop NULL/NA fields from a named list
+compact_list <- function(x) {
+  Filter(function(v) !(is.null(v) || (length(v) == 1 && is.atomic(v) && is.na(v))), x)
+}
+
+sites <- unique(events_all$site_id)
+
+site_objs <- purrr::map(sites, function(sid) {
+  evs_df <- events_all |>
+    dplyr::filter(site_id == sid) |>
+    dplyr::arrange(date)
+
+  # Only include required fields for each event type
+  evs_list <- purrr::pmap(
+    evs_df,
+    function(event_type, date, site_id, leaf_c_kg_m2 = NA_real_, frac_above_removed_0to1 = NA_real_,
+             frac_below_removed_0to1 = NA_real_, frac_above_to_litter_0to1 = NA_real_,
+             frac_below_to_litter_0to1 = NA_real_, amount_mm = NA_real_, method = NA_character_,
+             tillage_eff_0to1 = NA_real_, org_c_kg_m2 = NA_real_, org_n_kg_m2 = NA_real_,
+             nh4_n_kg_m2 = NA_real_, no3_n_kg_m2 = NA_real_,
+             crop = NA_character_, ...) {
+      base <- list(event_type = event_type, date = date)
+
+      # Add required fields per event type
+      if (event_type == "planting" && !is.na(leaf_c_kg_m2)) {
+        base$leaf_c_kg_m2 <- leaf_c_kg_m2
+        if (!is.na(crop)) base$crop <- crop
+      }
+      if (event_type == "harvest" && !is.na(frac_above_removed_0to1)) {
+        base$frac_above_removed_0to1 <- frac_above_removed_0to1
+        if (!is.na(frac_below_removed_0to1)) base$frac_below_removed_0to1 <- frac_below_removed_0to1
+        if (!is.na(frac_above_to_litter_0to1)) base$frac_above_to_litter_0to1 <- frac_above_to_litter_0to1
+        if (!is.na(frac_below_to_litter_0to1)) base$frac_below_to_litter_0to1 <- frac_below_to_litter_0to1
+        if (!is.na(crop)) base$crop <- crop
+      }
+      if (event_type == "irrigation" && !is.na(amount_mm) && !is.na(method)) {
+        base$amount_mm <- amount_mm
+        base$method <- method
+      }
+      if (event_type == "tillage" && !is.na(tillage_eff_0to1)) {
+        base$tillage_eff_0to1 <- tillage_eff_0to1
+      }
+      if (event_type == "fertilization" && !is.na(org_c_kg_m2)) {
+        base$org_c_kg_m2 <- org_c_kg_m2
+        if (!is.na(org_n_kg_m2)) base$org_n_kg_m2 <- org_n_kg_m2
+      }
+
+      compact_list(base)
+    }
+  )
+  list(
+    pecan_events_version = "0.1.0",
+    site_id = sid,
+    events = evs_list
+  )
+})
+
+# TODO add PEcAn Schema info
+
+# Validate JSON given schema
+# schema <- "data/pecan_events_schema_v0.1.0.json"
+# validator <- jsonvalidate::json_validator(schema)
+# json_txt_temp <- jsonlite::toJSON(site_objs, auto_unbox = TRUE)
+# if (!validator(json_txt_temp)) {
+#   stop("JSON does not match schema")
+# }
+
+# --- Write JSON --------------------------------------------------------------
+
+# Complete
+jsonlite::write_json(site_objs, path = output_json, pretty = FALSE, auto_unbox = TRUE)
+# Single site example
+jsonlite::write_json(site_objs[1:3], path = gsub(".json", "_3sites.json", output_json), pretty = TRUE, auto_unbox = TRUE)
+# When dealing with full dataset, may need to write to more performant files
+# #Sample
+# jsonlite::write_json(site_objs[1:100], path = sample_output_json, pretty = TRUE, auto_unbox = TRUE)
+
+# # Complete - compressed
+output_json_gz <- paste0(output_json, ".gz")
+gz_con <- gzfile(output_json_gz, "w")
+jsonlite::write_json(site_objs, path = gz_con, pretty = FALSE, auto_unbox = TRUE)
+close(gz_con)
+
+# --- Profiling End ---
+# Rprof(NULL)
+# summaryRprof("profiling.out")
+# --- End Profiling End ---