Impacts of Land Cover Change on Hydrology in a Mountainous Environment

Scott N. Miller, PhD Associate Professor

Chair, Graduate Programs in Hydrology

University of Wyoming, USA

Sustainable Management of Watersheds

The SUMAWA Project

Research Collaborators

► Univ. of Wyoming

S. Miller (PI)

S. Mooney

T. Baldyga

L. Dalles

► Egerton University

W. Shivoga (PI)

F. Lelo (co-PI)

C. Gichaba (co-PI)

C. Ouma

L. Chiuri

S. Inoti

• Univ. of Calif. – Davis M. Jenkins (co-PI)

► Moi University

M. Muchiri (co-PI) D. Liti

► Dep’t of Fisheries G. Macharia N. Gitonga

► Kenya Wildlife Service

R. Ndetei

► Utah State University S. Huckett

The River Njoro Watershed

KENYA

Nairobi

Njoro

Description of the Njoro Watershed

►Around 270 km2 with 250,000+ people

► In the Rift Valley

► Forested uplands

►Agricultural middle

►Urban lowlands

► Lake Nakuru National Park At outlet

Watershed Characteristics

Climate Change – East Africa

►Changes in precipitation patterns

Short rains and Long rains: increase in monthly rainfall amounts and intensity

Challenge: historical 30-year variability

►Increasing temperatures

0.2°C – 0.5°C per decade

►Current study: two predicted climate change scenarios

Research Methodology

►Long-term hydrologic data analysis

Installation of new equipment is ongoing

►4 rainfall, 2 runoff to date… more this year

►GIS data development

►SWAT modeling using GIS interface

►Couple output to other modeling tools

WEAP planning tool

Trade-Off economic modeling

Field Research

►Hydrologic sampling for analysis & modeling

Preliminary Findings

►Water quality (sediment, nutrients) already poor at upper end of watershed.

► Increased incidences of water-borne disease

Increased concentrations during dry season are pronounced

►Declining groundwater supplies, quality

Percentage Change in Annual Runoff in River Njoro Watershed; Data from 1961-1985

► Increase in runoff volume, BUT loss in access to water (e.g. increases water scarcity)

► We hypothesize that this is due to land cover change from mid-1990’s resulting in:

Loss of infiltration in upper watershed

Increased flashiness in runoff – downstream losses in water resources

1986-1989 1989-2000 2000-2003

-0.85 +31.34 +108.11

Remote Sensing

►11 images acquired from 1977 – 2004

►Focus on 3 anniversary images

1986, 1995, 2003

►Unsupervised / supervised classification

15 class system

►Change detection analysis

Landsat Image 2003

Change Detection

1986 Landsat Image

www.sumawa.org; Invited presentation to SENR student-faculty forum, Oct. 2003

Land Cover Change

Land Cover Change in Upper River Njoro Watershed (1986-2003)

Land

Cover

Class

1986

(ha)

1995

(ha)

2003

(ha)

Change

1986 – 2003

(ha)

Open

Water 0 0 1 1

Urban 275 438 502 227

Agriculture 10208 9902 11504 1296

Forest 11243 10110 7676 -3567

Grassland 4538 3017 4437 -101

GIS database construction * DEM, Soils, Landcover

AGWA – SWAT parameterization * CN, groundwater

Calibration on upper watershed * 1995 LC, 1990-1998 data * Nash-Sutcliffe * Annual (good), monthly (poor)

Comparison across time - upper * application of 1990-1998 rain, temp * assumed stationarity in time

Translation of parameter set to entire watershed

Rainfall-runoff time series analysis * Baseflow, missing data, weather

1986, 2003 Data

Automated Geospatial Watershed Assessment

(AGWA)

• Automated watershed modeling at multiple

scales using a GIS interface

– KINEROS & SWAT (modular)

• Investigate the impacts of land cover

change on runoff, erosion, water quality

• Targeted for use by research scientists,

management specialists

– technology transfer

– widely applicable

AGWA Summary

AGWA-SWAT Modeling on the Njoro

►Calibrated using 1995 Land Cover on the Upper Watershed (gaged)

►15+ year spin-up for rainfall

►Targeted 40% baseflow

►Climate

Elevation banding

Weather generator file for local conditions

Observed temperature

Input Data Layers

Soils

50m DEM

Land Cover

Calibration on Upper Watershed

►Data from 1990’s is best record

►Match with 1995 Land Cover data

►Poor data collection during high rainfall with serious implications for predictive modeling

►Calibrate on FC205 gage near Egerton University on the main stem below major confluences

Calibration on Upper Watershed

0

50

100

150

200

250

300

350

400

450

1990 1991 1992 1993 1994 1995 1996 1997 1998

YEAR

Q (

mm

)

Observed

Simulated

1997 removed due to poor data (>200 missing days)

Nash-Sutcliffe = 0.89

y = 0.84x + 37.3

R 2 = 0.92

0

50

100

150

200

250

300

350

400

450

0 50 100 150 200 250 300 350 400 450

Q Observed (mm)

Q S

imu

late

d (

mm

)

1:1 line

Comparison Across Time: 1995-2003

0

100

200

300

400

500

600

1990 1991 1992 1993 1994 1995 1996 1997 1998

1995 Simulation

2003 Simulation

Hydrologic Alterations - Simulated

►Overall trend: increased water yield

Increased surface discharge

Decreased groundwater discharge and percolation

►Altered timing is hard to determine but is implicated in the hydrologic changes

►Change is most dramatic after 1995

Modeling flow to the outlet

►Central portion heavily affected

► Increased surface runoff

►Altered timing and peak rates

►Overall net increase in water yield… decrease in groundwater recharge

Ongoing Challenges for Modeling

► Large runoff events create surge between gages; does not occur in low flows

►Huge missing data

►Groundwater knowledge

► Lack of gaging stations

0

20

40

60

80

100

120

140

160

0 5 10 15 20 25 30 35 40

Runoff Day

Dis

ch

arg

e (

cm

s)

#

#

Minimum and Maximum Annual Potentials (PPT) Current Climate: 724 – 1264 mm 4 – 379 mm Conservative Climate Change: 713 – 1275 mm 5 – 369 mm Extreme Climate Change: 690 – 1413 mm 10 – 444 mm

Overview

►Results are supportive of hypotheses

Strong link between forest & land cover and hydrologic response

►Long-term concern over water balance for human and natural systems

►Concerns over effects of GCC on resources

►Several areas for improvement

►Groundwork for integrated decision support