diff --git a/routes/conus_hydrology.py b/routes/conus_hydrology.py
index 07b62703..d245b60b 100644
--- a/routes/conus_hydrology.py
+++ b/routes/conus_hydrology.py
@@ -1,5 +1,6 @@
 import asyncio
 import io
+from pprint import pprint
 import numpy as np
 import xarray as xr
 import ast
@@ -29,6 +30,7 @@
 from csv_functions import create_csv
 from config import RAS_BASE_URL
 from . import routes
+import statistics
 
 coverages = {
     "stats": ["conus_hydro_segments_stats"],
@@ -1002,14 +1004,12 @@ def run_get_conus_hydrology_gauge_info():
         return render_template("500/server_error.html"), 500
 
 
-@routes.route("/conus_hydrology/hydroviz/<stream_id>/<model>")
-def fetch_all_hydroviz_route(stream_id, model):
+@routes.route("/conus_hydrology/hydroviz/<stream_id>")
+def fetch_all_hydroviz_route(stream_id):
     """
-    Function to fetch all data for the hydrology visualization for a given stream ID and model.
-    Maurer historical baseline data is included in every return.
+    Function to fetch all data for the hydrology visualization for a given stream ID.
     Args:
         stream_id (str): Stream ID for the hydrology data
-        model (str): Model for projected data, only affects stats for tables.
     Returns:
         JSON response with the following top-level keys, which correspond to different sections
         of the hydroviz webapp and contain only the data necessary to populate those sections.
@@ -1017,148 +1017,374 @@ def fetch_all_hydroviz_route(stream_id, model):
             "hydrograph": ...,
             "id": ...,
             "monthly_flow": ...,
+            "min_max_flow_dates": ...,
             "name": ...,
             "stats": ...,
             "summary": ...
         }
-
     """
-    # Use this to validate the model provided in the URL.
-    projected_models = [
-        "ACCESS1-0",
-        "BCC-CSM1-1",
-        "BNU-ESM",
-        "CCSM4",
-        "GFDL-ESM2G",
-        "GFDL-ESM2M",
-        "IPSL-CM5A-LR",
-        "IPSL-CM5A-MR",
-        "MIROC-ESM",
-        "MIROC-ESM-CHEM",
-        "MIROC5",
-        "MRI-CGCM3",
-        "NorESM1-M",
-    ]
-
-    if model not in projected_models:
-        return render_template("400/bad_request.html"), 400
 
     stats_response = run_get_conus_hydrology_stats_data(stream_id)
-    modeled_response = run_get_conus_hydrology_modeled_climatology(stream_id)
+    climatology_response = run_get_conus_hydrology_modeled_climatology(stream_id)
+
+    # Projected eras to use for the hydrograph and monthly flow charts.
+    chart_eras = ["2016-2045", "2046-2075", "2071-2100"]
 
     # If either response is an error page, return it.
-    for response in [stats_response, modeled_response]:
+    for response in [stats_response, climatology_response]:
         if isinstance(response, tuple):
             return response
 
-    try:
-        stats = stats_response.get_json()
-        modeled = modeled_response.get_json()
+    # try:
+    # Fetch all needed data.
+    stats = stats_response.get_json()
+    climatology = climatology_response.get_json()
+
+    # Convert static stats to "Maurer plus projected delta".
+    static_stats = stats["data"]["static"]
+    maurer_plus_delta_stats = {}
+    for model in static_stats.keys():
+        if model not in maurer_plus_delta_stats:
+            maurer_plus_delta_stats[model] = {}
+        for scenario in static_stats[model].keys():
+            if scenario in ["historical", "rcp26"]:
+                continue
+            if scenario not in maurer_plus_delta_stats[model]:
+                maurer_plus_delta_stats[model][scenario] = {}
+            for era in static_stats[model][scenario].keys():
+                if era not in maurer_plus_delta_stats[model][scenario]:
+                    maurer_plus_delta_stats[model][scenario][era] = {}
+                # print("##### KEYS #######")
+                # pprint(static_stats[model][scenario][era].keys())
+                for stat in static_stats[model][scenario][era].keys():
+                    maurer_historical = static_stats["Maurer"]["historical"][
+                        "1976-2005"
+                    ][stat]
+                    modeled_historical = static_stats[model]["historical"]["1976-2005"][
+                        stat
+                    ]
+                    modeled_projected = static_stats[model][scenario][era][stat]
+                    projected_delta = modeled_projected - modeled_historical
+                    maurer_plus_delta = round(maurer_historical + projected_delta, 3)
+
+                    ### Temporary fallback to raw projected data, not Maurer + delta method.
+                    ### TODO: Figure out how to make the Maurer + delta method work without unrealistic values.
+                    # # These stats represent days per year, so cannot exceed 366.
+                    # if (
+                    #     stat
+                    #     in [
+                    #         "dh15",
+                    #         "dl16",
+                    #         "lf1",
+                    #         "ra8",
+                    #         "spr_ord",
+                    #         "sum_ord",
+                    #         "th1",
+                    #         "tl1",
+                    #     ]
+                    #     and maurer_plus_delta > 366
+                    # ):
+                    #     maurer_plus_delta = 366
+
+                    # # No stat can be negative except for ra3.
+                    # if stat != "ra3" and maurer_plus_delta < 0:
+                    #     maurer_plus_delta = 0
+                    # elif stat == "ra3" and maurer_plus_delta > 0:
+                    #     maurer_plus_delta = 0
+
+                    # maurer_plus_delta_stats[model][scenario][era][
+                    #     stat
+                    # ] = maurer_plus_delta
+                    maurer_plus_delta_stats[model][scenario][era][
+                        stat
+                    ] = modeled_projected
+
+    # pprint(maurer_plus_delta_stats)
+
+    # Convert static climatology to "Maurer plus projected delta".
+    static_climatology = climatology["data"]["static"]
+    maurer_plus_delta_climatology = {}
+    for model in static_climatology.keys():
+        if model not in maurer_plus_delta_climatology:
+            maurer_plus_delta_climatology[model] = {}
+        for scenario in static_climatology[model].keys():
+            if scenario in ["historical", "rcp26"]:
+                continue
+            if scenario not in maurer_plus_delta_climatology[model]:
+                maurer_plus_delta_climatology[model][scenario] = {}
+            for era in static_climatology[model][scenario].keys():
+                if era not in maurer_plus_delta_climatology[model][scenario]:
+                    maurer_plus_delta_climatology[model][scenario][era] = []
+                for i in range(len(static_climatology[model][scenario][era])):
+                    doy_stats = {}
+                    for stat in static_climatology[model][scenario][era][i].keys():
+                        maurer_historical = static_climatology["Maurer"]["historical"][
+                            "1976-2005"
+                        ][i][stat]
+                        modeled_historical = static_climatology[model]["historical"][
+                            "1976-2005"
+                        ][i][stat]
+                        modeled_projected = static_climatology[model][scenario][era][i][
+                            stat
+                        ]
+                        projected_delta = modeled_projected - modeled_historical
+                        maurer_plus_delta = round(
+                            maurer_historical + projected_delta, 3
+                        )
+
+                        ### Temporary fallback to raw projected data, not Maurer + delta method.
+                        ### TODO: Figure out how to make the Maurer + delta method work without unrealistic values.
+                        # doy_stats[stat] = maurer_plus_delta
+                        doy_stats[stat] = modeled_projected
+                    maurer_plus_delta_climatology[model][scenario][era].append(
+                        doy_stats
+                    )
+
+    ########## Populate arrays for hydrograph. ##########
+
+    hydrograph = {
+        "historical": {},
+        "projected": {},
+    }
 
-        # The hydrograph and monthly mean flow charts use this scenario and era.
-        scenario = "rcp85"
-        era = "2046-2075"
+    historical_climatology = climatology["data"]["static"]["Maurer"]["historical"][
+        "1976-2005"
+    ]
+    hydrograph_historical = {
+        "doy_min": list(map(lambda x: x["doy_min"], historical_climatology)),
+        "doy_mean": list(map(lambda x: x["doy_mean"], historical_climatology)),
+        "doy_max": list(map(lambda x: x["doy_max"], historical_climatology)),
+    }
+    hydrograph["historical"] = hydrograph_historical
+
+    # Get min/mean/max values for each DOY across all projected models.
+    for era in chart_eras:
+        if era not in hydrograph["projected"]:
+            hydrograph["projected"][era] = {}
+        for scenario in ["rcp45", "rcp60", "rcp85"]:
+            if scenario not in hydrograph["projected"][era]:
+                hydrograph["projected"][era][scenario] = {
+                    "doy_min_min": [],
+                    "doy_mean_min": [],
+                    "doy_mean_mean": [],
+                    "doy_mean_max": [],
+                    "doy_max_max": [],
+                }
+            for i in range(366):
+                doy_mins = []
+                doy_means = []
+                doy_maxes = []
+                for model_dict in maurer_plus_delta_climatology.values():
+                    if scenario not in model_dict:
+                        continue
+                    doy_mins.append(model_dict[scenario][era][i]["doy_min"])
+                    doy_means.append(model_dict[scenario][era][i]["doy_mean"])
+                    doy_maxes.append(model_dict[scenario][era][i]["doy_max"])
 
-        hydrograph_min = []
-        hydrograph_mean = []
-        hydrograph_max = []
+                hydrograph["projected"][era][scenario]["doy_min_min"].append(
+                    round(min(doy_mins), 3)
+                )
+                hydrograph["projected"][era][scenario]["doy_mean_min"].append(
+                    round(min(doy_means), 3)
+                )
+                hydrograph["projected"][era][scenario]["doy_mean_mean"].append(
+                    round(statistics.mean(doy_means), 3)
+                )
+                hydrograph["projected"][era][scenario]["doy_mean_max"].append(
+                    round(max(doy_means), 3)
+                )
+                hydrograph["projected"][era][scenario]["doy_max_max"].append(
+                    round(max(doy_maxes), 3)
+                )
 
-        doy_min = None
-        doy_max = None
-        doy_mean = None
+    ########## Populate arrays for monthly modeled flow rate chart. ##########
 
-        hydrograph_historical = {}
-        historical = modeled["data"]["static"]["Maurer"]["historical"]["1976-2005"]
+    monthly_flow = {
+        "historical": {},
+        "projected": {},
+    }
 
-        hydrograph_historical["doy_min"] = list(
-            map(lambda x: round(x["doy_min"]), historical)
-        )
-        hydrograph_historical["doy_mean"] = list(
-            map(lambda x: x["doy_mean"], historical)
-        )
-        hydrograph_historical["doy_max"] = list(
-            map(lambda x: round(x["doy_max"]), historical)
-        )
+    monthly_flow_keys = [
+        "ma12",
+        "ma13",
+        "ma14",
+        "ma15",
+        "ma16",
+        "ma17",
+        "ma18",
+        "ma19",
+        "ma20",
+        "ma21",
+        "ma22",
+        "ma23",
+    ]
 
-        del modeled["data"]["static"]["Maurer"]
-
-        # Get min/mean/max values for each DOY across all projected models.
-        for i in range(366):
-            unset = True
-            for model_dict in modeled["data"]["static"].values():
-                if unset:
-                    doy_min = model_dict[scenario][era][i]["doy_min"]
-                    doy_max = model_dict[scenario][era][i]["doy_max"]
-                    doy_mean = model_dict[scenario][era][i]["doy_mean"]
-                    unset = False
+    # Get historical data for each month.
+    for key in monthly_flow_keys:
+        monthly_flow["historical"][key] = stats["data"]["static"]["Maurer"][
+            "historical"
+        ]["1976-2005"][key]
+
+    # Populate lists of values for each month for each projected model.
+    # These values will be used to generate box plots in the webapp.
+    for era in chart_eras:
+        if era not in monthly_flow["projected"]:
+            monthly_flow["projected"][era] = {}
+        for scenario in ["rcp45", "rcp60", "rcp85"]:
+            if scenario not in monthly_flow["projected"][era]:
+                monthly_flow["projected"][era][scenario] = {}
+            for model_stats in maurer_plus_delta_stats.values():
+                # print("########### model_stats ############")
+                # pprint(model_stats)
+                if scenario not in model_stats:
                     continue
-                else:
-                    if model_dict[scenario][era][i]["doy_min"] < doy_min:
-                        doy_min = model_dict[scenario][era][i]["doy_min"]
-                    if model_dict[scenario][era][i]["doy_max"] > doy_max:
-                        doy_max = model_dict[scenario][era][i]["doy_max"]
-                    doy_mean += model_dict[scenario][era][i]["doy_mean"]
-
-            hydrograph_min.append(round(doy_min))
-            hydrograph_mean.append(round(doy_mean / len(modeled["data"]["static"]), 3))
-            hydrograph_max.append(round(doy_max))
-
-        monthly_flow_keys = [
-            "ma12",
-            "ma13",
-            "ma14",
-            "ma15",
-            "ma16",
-            "ma17",
-            "ma18",
-            "ma19",
-            "ma20",
-            "ma21",
-            "ma22",
-            "ma23",
-        ]
-
-        monthly_flow = {"historical": {}, "projected": {}}
-
-        # Get historical data for each month.
-        for key in monthly_flow_keys:
-            monthly_flow["historical"][key] = stats["data"]["static"]["Maurer"][
-                "historical"
-            ]["1976-2005"][key]
-
-        # Populate lists of values for each month for each projected model.
-        # These values will be used to generate box plots in the webapp.
-        for model_key, model_stats in stats["data"]["static"].items():
-            # Skip Maurer, which is used only for historical baselines.
-            if model_key == "Maurer":
-                continue
-            for key in monthly_flow_keys:
-                if key not in monthly_flow["projected"]:
-                    monthly_flow["projected"][key] = []
-                monthly_flow["projected"][key].append(model_stats[scenario][era][key])
-
-        # Stats for the tables in the webapp, only for the requested model.
-        table_stats = {
-            "historical": stats["data"]["static"]["Maurer"]["historical"],
-            "projected": stats["data"]["static"][model][scenario],
-        }
-
-        response = {
-            "hydrograph": {
-                "historical": hydrograph_historical,
-                "projected": {
-                    "doy_min": hydrograph_min,
-                    "doy_mean": hydrograph_mean,
-                    "doy_max": hydrograph_max,
-                },
+                # print("##############################")
+                # pprint(model_stats[scenario][era])
+                for key in monthly_flow_keys:
+                    if key not in monthly_flow["projected"][era][scenario]:
+                        monthly_flow["projected"][era][scenario][key] = []
+                    monthly_flow["projected"][era][scenario][key].append(
+                        model_stats[scenario][era][key]
+                    )
+
+    ########## Populate arrays for max flow date chart. ##########
+
+    min_max_flow_dates = {
+        "historical": {
+            "min": {
+                "flow": None,
+                "date": None,
             },
-            "id": stats["id"],
-            "name": stats["name"],
-            "monthly_flow": monthly_flow,
-            "stats": table_stats,
-            "summary": stats["summary"],
-        }
-        return jsonify(response)
+            "max": {
+                "flow": None,
+                "date": None,
+            },
+        },
+        "projected": {},
+    }
 
-    except Exception as exc:
-        return render_template("500/server_error.html"), 500
+    # Get historical data for min and max flow date.
+    min_max_flow_dates["historical"]["min"]["flow"] = stats["data"]["static"]["Maurer"][
+        "historical"
+    ]["1976-2005"]["dl1"]
+    min_max_flow_dates["historical"]["min"]["date"] = stats["data"]["static"]["Maurer"][
+        "historical"
+    ]["1976-2005"]["tl1"]
+    min_max_flow_dates["historical"]["max"]["flow"] = stats["data"]["static"]["Maurer"][
+        "historical"
+    ]["1976-2005"]["dh1"]
+    min_max_flow_dates["historical"]["max"]["date"] = stats["data"]["static"]["Maurer"][
+        "historical"
+    ]["1976-2005"]["th1"]
+
+    # Populate lists of values for max flow date for each projected model.
+    for era in chart_eras:
+        if era not in min_max_flow_dates["projected"]:
+            min_max_flow_dates["projected"][era] = {}
+        for scenario in ["rcp45", "rcp60", "rcp85"]:
+            if scenario not in min_max_flow_dates["projected"][era]:
+                min_max_flow_dates["projected"][era][scenario] = {
+                    "min": {
+                        "flow": [],
+                        "date": [],
+                    },
+                    "max": {
+                        "flow": [],
+                        "date": [],
+                    },
+                }
+            for model_stats in maurer_plus_delta_stats.values():
+                if scenario not in model_stats:
+                    continue
+
+                min_max_flow_dates["projected"][era][scenario]["min"]["flow"].append(
+                    model_stats[scenario][era]["dl1"]
+                )
+                min_max_flow_dates["projected"][era][scenario]["min"]["date"].append(
+                    model_stats[scenario][era]["tl1"]
+                )
+                min_max_flow_dates["projected"][era][scenario]["max"]["flow"].append(
+                    model_stats[scenario][era]["dh1"]
+                )
+                min_max_flow_dates["projected"][era][scenario]["max"]["date"].append(
+                    model_stats[scenario][era]["th1"]
+                )
+
+    ########## Calculate stats for the stats table. ##########
+
+    table_stats = {
+        "historical": {},
+        "projected": {},
+    }
+
+    table_stats["historical"] = stats["data"]["static"]["Maurer"]["historical"]
+
+    all_stats = {}
+    mid_stats = {}
+    for era in chart_eras:
+        for model_stats in maurer_plus_delta_stats.values():
+            for scenario in model_stats.keys():
+                if scenario in ["historical", "rcp26"]:
+                    continue
+                if era not in model_stats[scenario]:
+                    continue
+                for stat in model_stats[scenario][era].keys():
+                    if era not in all_stats:
+                        all_stats[era] = {}
+                    if stat not in all_stats[era]:
+                        all_stats[era][stat] = []
+                    all_stats[era][stat].append(model_stats[scenario][era][stat])
+                    if scenario == "rcp60":
+                        if era not in mid_stats:
+                            mid_stats[era] = {}
+                        if stat not in mid_stats[era]:
+                            mid_stats[era][stat] = []
+                        mid_stats[era][stat].append(model_stats["rcp60"][era][stat])
+
+    for era in all_stats.keys():
+        if era not in table_stats["projected"]:
+            table_stats["projected"][era] = {}
+        for stat in all_stats[era].keys():
+            all_values = all_stats[era][stat]
+            mid_values = mid_stats[era][stat]
+            if "min" not in table_stats["projected"][era]:
+                table_stats["projected"][era]["min"] = {}
+            if "max" not in table_stats["projected"][era]:
+                table_stats["projected"][era]["max"] = {}
+            if "mid" not in table_stats["projected"][era]:
+                table_stats["projected"][era]["mid"] = {}
+            table_stats["projected"][era]["min"][stat] = round(min(all_values), 3)
+            table_stats["projected"][era]["max"][stat] = round(max(all_values), 3)
+            table_stats["projected"][era]["mid"][stat] = round(
+                statistics.mean(mid_values), 3
+            )
+
+    gauge_id = None
+    h8_outlet = False
+    huc8 = None
+
+    gdf = asyncio.run(get_features(stream_id))
+    if not isinstance(gdf, tuple):
+        if gdf.loc[0].h8_outlet == 1:
+            h8_outlet = True
+        if gdf.loc[0].GAUGE_ID != "NA":
+            gauge_id = gdf.loc[0].GAUGE_ID
+        huc8 = gdf.loc[0].huc8
+
+    response = {
+        "gauge_id": gauge_id,
+        "h8_outlet": h8_outlet,
+        "huc8": huc8,
+        "hydrograph": hydrograph,
+        "id": stats["id"],
+        "name": stats["name"],
+        "monthly_flow": monthly_flow,
+        "min_max_flow_dates": min_max_flow_dates,
+        "stats": table_stats,
+        "summary": stats["summary"],
+    }
+
+    return jsonify(response)
+
+    # except Exception as exc:
+    #     return render_template("500/server_error.html"), 500