# data[].attributes.body
Nitrogen

Phosphorus

Pesticides

# data[].attributes.body
Sediment

Biological debris in streams

# data[].attributes.body
E. coli from wildlife

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Metals

Sediment

Acid mine drainage

# data[].attributes.body
Increased runoff

Pet waste

Loss of riparian vegetation

Increased types of pollutants (oil/gas, stuff sent down storm drains, metals from brakes)

Pharmaceuticals and personal care products

Septic systems

Waste water treatment plants discharge

Dumping yard waste

# data[].attributes.body
Increased runoff

Loss of riparian vegetation

Roads and surface disturbances away from stream as well

# data[].attributes.body
Animal waste

Increased nutrients

Loss of riparian Vegetation

Compacted banks

Increased erosion

# data[].attributes.body
Cooling systems that require water

# data[].attributes.body
Loss of riparian vegetation

Roads lead to increased erosion

# data[].attributes.body
High temperature water discharge

# data[].attributes.body
Fertilizers

Pesticides

Sediment

Oil and gas

PPCPs

Stuff down storm drains

Nitrous oxides from combustion engines (autos)

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Use - Irrigation, Feedlots, and Pastures

# data[].attributes.subject
Use - Irrigation, Feedlots, and Pastures

# data[].attributes.headline
Use - Housing and Commercial Developments

# data[].attributes.subject
Use - Housing and Commercial Developments

# data[].attributes.body
Match the different types of POLLUTANTS and IMPACTS of land use and pollution with the correct watershed location. Use these impacts as evidence to defend your data in your hypothesis.

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Rank each factor as LOW, NEUTRAL, or HIGH. Then, drag to match with the correct watershed location. Finally, state a HYPOTHESIS for why these were matched.

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DO NOT MOVE PHOTOS. Match the different land use with the correct watershed location.

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Snowpack

High elevation

Riparian vegetation

# data[].attributes.body
Temperature: _23C__

Turbidity: _22NTU__

Nitrates: _8mg/L___

pH level: __7__

Dissolved Oxygen: __5.5mg/L___

HYPOTHESIS: its temperature is good for cold water, but its turbidity  may not be the safest

# data[].attributes.body
Temperature: _21 C__

Turbidity: _ 28NTU___

Nitrates: _3mg/L___

pH level: __7.5_

Dissolved Oxygen: _7.0mg/L__

HYPOTHESIS: it may fit this area because erosion and turbidity are slightly higher than normal. In addition, there is some pollution present with the nitrate of three.

# data[].attributes.body
Temperature: ___16°C___

Turbidity: __4NTUs____

Nitrates: __.05mg/l____

pH level: ___6___

Dissolved Oxygen: _8.5_____

HYPOTHESIS: It would be the river because snowfall tends to be drinkable. The temperature tends to be cooler in these areas.

# data[].attributes.body
Temperature: ___19___

Turbidity: ___35NTUs___

Nitrates: ___1.5mg/l___

pH level: __4.5____

Dissolved Oxygen: _7.5mg/l_____

HYPOTHESIS: this area had the lowest temp.

# data[].attributes.body
Temperature: ___22°C___

Turbidity: _15NTUs_____

Nitrates: ___6.55mg/l___

pH level: ___7___

Dissolved Oxygen: _6mg/l_____

HYPOTHESIS: This area had the highest turbity

# data[].attributes.body
Temperature: __28°C____

Turbidity: __12NTUs__

Nitrates: _2mg/l_____

pH level: __7____

Dissolved Oxygen: ___5.5mg/l___

HYPOTHESIS: It would be matched here because the pH and temperature are normal. As a result, everything would be pretty normal-looking.

# data[].attributes.headline
Do not scroll further down past this point!

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Do not scroll further down past this point!