Modeling of hydrological processes and water use across Northern - PowerPoint PPT Presentation

Modeling of hydrological processes and water use across Northern Eurasia Alexander Shiklomanov 1,2,3 and Alexander Prusevich 1 1-Water Systems Analysis Group, EOS, University of New Hampshire, USA 2-Laboratory of Hydrological Cycle, Shirshov Institute of Oceanology RAS, Moscow, Russia 3-Arctic and Antarctic Research Institute, Saint Petersburg, Russia http://www.wsag.unh.edu ENVIROMIS-2016 Tomsk, July 11-16, 2016

WBM-TrANS Water Balance Model - Transport from Antropogenic and Natural Systems (PDL WBM)

General structure of Water Balance Model - Transport from Antropogenic and Natural Systems (WBM-TrANS) • WBM/WTM (old model) – physically based macroscale hydrological model (Vörösmarty, 1998) – WTM Routing based on river network (STN) • WBM-TrANS (new model) – WBM + irrigation + reservoirs+ diversions+ water withdrawal (industrial, domestic, livestocks) + multiple (dynamic) land cover/use ; glacier discharge, hourly/daily/monthly time step (2 routing models, 3 ET functions), coupled with permafrost GPL model (under development)

WBM-TrANS Flowchart Input Parameters Model Code Output Variables and from File, Spreadsheet Datasets Core version, Branched versions or Database RIMS (the Magic Table) Datasets, Datasets Metadata, Visualization, Analysis, Data Aggregation, Data Manipulation Fundamental WB Processes Water Routing Water Use Model Components to generate runoff by river network for human needs • General Land option • Precipitation • Instant Runoff • Irrigation from • Land Cover types • Snow/Glacier melt • Delayed Runoff stream and/or • MIRCA Crops (64 ) • Intercept • Downstream flow ground water • Irrigated Subcrops • Evapotranspiration • Flow components • Industrial use • Rainfed Subcrops • Soil processes • Reservoirs/Lakes • Domestic use • Rice Paddies • Permafrost • Interbasin transfer • Pollution • Fallow Lands • Infiltration • Irrigation transfer • Hydrobiochemistry • Impervious Lands • Surface Runoff • Evaporation • Ecosystem impacts • Permafrost • Baseflow Runoff • Sedimentation • Energy production

NEESPI RIMS Regional Integrated Mapping and Analysis System http://neespi.sr.unh.edu/maps 1) data search/selection, spatial navigation, metadata link, etc.; 2) coordinate and map data value reader; 3) pixel query tool (i-tool) gets coordinates, country, watershed, and map data value; 4) time series navigation tool; 5) map size and base layer choices; 6) data interpolation and shading tools; 7) point/station data list with clickable symbols that open station pages in a separate browser window; 8) fold-out section to run the Data Calculator application to perform mathematical and logical functions over gridded or vector datasets;.

Summary of RIMS data holdings Current Dataset Count Earth System Science Key Sources Examples of Major Parameters Data Category Source + Source DataCube Discharge, runoff, river networks, Hydrology UNH, CCNY 200 250 irrigation, dams NASA, NOAA, UDel, Temperature, precipitation, Past and Present 70 210 Princeton U. evapotranspiration (ET), heat Climate radiation, pressure, wind NCEP, MERRA 62 160 Future Climate and Temperature, precipitation, ET, snow, IPCC , UNH 680 4100 Hydrology runoff, discharge MODIS, UNH, Vegetation indices, soil moisture, Remote Sensing 48 60 UOklahoma clouds, snow, fires Elevation, bathymetry, Blue Marble, Physical Geography NASA, USGS, UNH 28 22 Lon/Lat Oceanography NOAA, NCOF SST, sea ice 3 4 Land cover, vegetation, permafrost, Land Cover UM, NASA, USGS 60 80 freeze/thaw Sociology and CIESIN, World Bank, US Population, GDP, industry, 30 60 Economics CIA, UNH mortality/birth/malnutrition rates Crop land, crops, fertilizer loads, Agriculture UWisc, Various 160 200 greenhouse emissions Watershed, sea/ocean catchments, Polygon Masks UNH continents, countries, administrative 18 18 units Station Data UNH, AGS Hydrology, climate, public health 8 8 Total ~1400 ~5100

Topological River Networks WBM-TrANS works with any topological river networks in any projections and in any basin subsets. Some common TRNs- STN (Simulated Topological Networks), UNH. • Resolutions*: 6’ and 30’ • HydroSHEDS ( Hydro logical data and maps based • on SH uttle E levation D erivatives at multiple S cales), Canada. Resolutions*: 3” and 15” • Hydro1k , USGS. • Resolutions*: 30” and 1 km • DRT (Dominant River Tracing), Europe. • Resolutions: 1/16°, 1/8°, 1/2°, 1°, 2°. • * Can be downscaled to coarser resolutions (Fekete et al., 2001) Network parameters- Direction • Stream Order • Basin ID • Basin Attributes • Cell Table • Distance to mouth •

New features of WBM-TrANS

GRanD ang NID Dam Databases GRanD database- GRanD Extent: Global Total: 6,885 dams Russia: 52 dams Params: 56 NID database- Extent: USA Total: 83,987 dams Params: 65 Both can be used in WBM-TrANS NID

� � Reservoir Operating Rules Reservoir Operating Rule 5 4,5 Discharge release (Q/Q mean over 5 past years ) 4 3,5 Exponential Release Rule 3 2,5 2 𝐸 = 𝐸 $%& 𝑇 ( + 𝑚𝑜 𝑙𝑇 -/ / 0 Optimal reservoir level + 1 𝑏𝑢 𝑇 < 𝑇 678%$9: 1,5 Average Annual Discharge (5 yrs) 1 @ 𝑏𝑢 𝑇 ≥ 𝑇 678%$9: 𝐸 = 𝑓𝑦𝑞 𝑐 𝑇 − 𝑇 678%$9: 0,5 Logarithmic Release Rule B where 𝑙 = 𝑓𝑦𝑞 1 − 𝐸 $%& 𝑇 ( − 1 , b = 10, α = 2/3, 0 / CDEFGHIJ/ K0 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1 and 0.1< S R <1 is regulatory capacity (a ratio between annual Reservoir Level (Storage/Capacity) cumulative flow volume and the reservoir capacity). Table of suggested parameters for Equation (1) – As of now, only Generic rule is coded in WBM. Dam Purpose b α Comment Generic 0.2 0.8 10 2/3 Works for most of dams Hydropower 0.2 0.9 40 1 Steeper curve to keep high water level Irrigation 0.1 0.8 10 1/2 Flatter curve to have more even discharge Natural Lake 0.0 0.5 1.6 2/3 Smooth curve, release is smoothed inflow

USGS National Inventory of Dams In New England Old Mill & Dam, Durham, NH

Merrimack River (12,005 km 2 ) Connecticut River (25,020 km 2 ) 900 1800 GRDC, observed GRDC, observed WBM, with dams. Nash-Sutcliffe Coef. = 0.79 WBM, with dams. Nash-Sutcliffe Coef. = 0.82 800 1600 WBM, no dams. Nash-Sutcliffe Coef. = 0.72 WBM, no dams. Nash-Sutcliffe Coef. = 0.72 700 1400 600 1200 Discharge. m 3 /sec Discharge. m 3 /sec 500 1000 400 800 300 600 200 400 100 200 0 0 1979 1980 1981 1982 1983 1984 1979 1980 1981 1982 1983 1984 Year Year

Glacial Melt water Global Inventory of Glaciers (GIG) Database (UAF/UNH) Extent: Global Total: 200,302 glaciers Russia: 4299 glaciers Params: unknown Grid Cell Area In WBM-TrANS Glacier Glacier area gets subtracted Area from grid cell area and melt water from GIG DB is added to its runoff Melt water release point from the Glacier

Gridded glacier discharge mean yearly climatology based on ERA-40 climate data and UAF glacier model simulation

Snowmelt computation in mountainous regions Elevation/Snow Bands Snow pack size depends non-linearly on altitude, via Ø precipitation and temperature. In temperate mountainous regions, with seasonally- Ø varying snow line, using the average elevation, temperature, and precipitation over the entire grid cell gives wrong answer. How it works: Ø Subdivide grid cell into arbitrary number of elevation o bands (we use 200 m intervals from 0 to 5 km elev.). Within each band, meteorologic forcings are lapsed o from grid cell average elevation to band's elevation. Geographic locations or configurations of elevation o bands are not considered; WBM lumps all areas of same elevation range into 1 band. Fluxes and storages from the bands are averaged o together (weighted by area fraction) to give grid-cell average for writing to output files. Use of elevation and snow bands is less necessary Ø when running WBM at high resolution (e.g. 6 min network or higher). When snow bands are used on 30 min network, the Ø spring snow melting season extends from about 10 days (no snow bands) to at least 4 weeks (with snow bands) in mountainous regions.

Irrigation: Water is applied when the depth of the water table in the soil reaches a crop-dependent threshold

Land Partitioning Model in a Grid Cell Example of a Grid Cell Fractional Partitioning of Landcovers by type Natural and Anthropogenic (non-crop) Landcovers- Can be a Time Series dataset. Urban Land Grasslands Evergreen Presently we use 14 MODIS LC Needleleaf Mixed Forest types. Each type has its own set of Forest WBM parameters (e.g. root depth) that results in LC dependent runoff. Rainfed Croplands- Fractional Partitioning of Rainfed Crops Can be a Time Series dataset. Corn Wheat Rye Fallow Land Vine Presently we use 64 MIRCA crop types. Each crop has its own WBM. Fractional Partitioning of Irrigated Crops Irrigation Equipped Area- Can be a Time Series dataset. Presently we use 32 MIRCA crop Rice Corn Vine Fallow Land types. Each crop has its own WBM. All crops allow crop rotation, and off-season fallow lands.

Simulation of irrigation water demand Irrigation Water Demand Harvested irrigation area High 280,000 High 800 Low 0 Low 0.00 Harvested irrigation area (ha) from MIRCA2000 (left) and average Irrigation Water Demand (mm/year) from WBM-TRANS. On all maps, lines represent province boundaries.